The current methods used to detect breast cancer spread (metastases) are crude and fail to identify a large number of patients with metastatic disease. In a patient diagnosed with breast cancer, treatment includes the surgical removal of the tumor as well as the removal of 10-30 lymph nodes (LN) located under the arm. This is done because cancer first spreads to the LN and removing LN metastases decreases tumor recurrence and may increase survival. One small slice of each lymph node is typically analyzed by pathologists to determine if it contains tumor cells. However, this type of analysis misses disease in many patients since 1/3-1/2 of women with no detectable metastases in their LN still die of breast cancer. Furthermore, by the time that women with breast cancer have symptoms of metastases or detectable tumors by x-ray, there is too much cancer for even the strongest therapies to cure.
This study will evaluate a more sensitive way to identify cancer cells in the LN and blood of breast cancer patients. Reverse transcriptase-polymerase chain reaction (RT-PCR) is a detection technique that is 10-100 times more sensitive than routine pathology methods and can detect one tumor cell among one million normal cells. A major obstacle to the clinical use of RT-PCR to detect breast cancer cells has been the lack of a specific marker that is present in all breast cancer cells from all patients but is absent from normal LN and blood. We have evaluated many markers in laboratory studies in order to develop a panel of specific sensitive markers best suited for breast cancer detection and have identified two outstanding markers of breast cancer that can distinguish tumor cells from normal LN and blood cells.
It is impractical and expensive to analyze all of the removed LN for disease. However, sentinel node biopsy involves the surgical removal of the one or two ¿sentinel¿ lymph nodes (SLN) and allows RT-PCR analysis to be applied to the LN most likely to contain disease. We have initiated a multi-institutional trial for evaluating SLNB in breast cancer patients and will analyze banked and newly acquired tumor and LN specimens. We will also examine blood for metastasizing tumor cells and marker proteins. We have analyzed SLN from 92/500 patients enrolled in our trial. Our markers are detected in 94%-100% node-positive breast cancer patients and have potentially upstaged 20%-50% patients deemed as node-negative by histology. These excellent preliminary results underscore the merit and promise of our approach.
Our hypothesis in the proposed study is that RT-PCR analysis for these specific markers will provide a more sensitive and accurate detection of cancer that has spread to the blood and lymph nodes of breast cancer patients. We will (1) analyze patient tumor and SLN specimens by standard pathology and by RT-PCR for detection of markers inside tumor cells; (2) compare RT-PCR to standard analysis for sensitivity, accuracy, and for the ability to predict cancer recurrence and survival at 2- and 4-year follow-up; (3) analyze blood specimens taken at the time of surgery and at regular intervals after surgery for circulating tumor cells (by RT-PCR); (4) evaluate whether the detection of tumor markers in blood specimens by RT-PCR can predict disease recurrence and survival; and (5) evaluate additional marker candidates in the laboratory and add the most promising to the RT-PCR panel to ensure detection of breast cancer in all patients.
More accurate analysis of LN may identify histologically node-negative patients actually at risk for recurrence (who are most likely to benefit from aggressive therapy) and truly node-negative patients (who may not need to be exposed to the risks and morbidity of aggressive therapy). Analysis of peripheral blood for circulating tumor cells and for marker proteins may enable more accurate staging presurgery and may allow the improved and timely detection of metastatic disease after surgery. We are confident that our translational research approach will result in substantial improvements in the detection of occult disease.