STUDY OBJECTIVES: The survival of patients with surgically resected stage I non-small cell lung cancer (NSCLC) is not optimal, probably because of unsuspected systemic occult tumor dissemination. The current applied technologies and methods for scanning the body and examining lymph nodes for tumor cells have broadly recognized limitations. Several studies have reported that it is possible to detect occult lymph node metastases (micrometastases) using more sensitive methods such as immunohistochemistry or molecular technology. The aim of our study was to evaluate the utility of quantitative real-time reverse-transcriptase polymerase chain reaction (RT-PCR) for carcinoembryonic antigen (CEA) messenger RNA (mRNA) for detection of lymph node micrometastases and its impact on disease-free interval. METHODS: Quantitative real-time RT-PCR for CEA mRNA was performed on primary lung tumors and regional lymph nodes from 44 surgically resected NSCLC patients classified as clinical stage I. Fourteen lymph nodes from five patients without malignancy were used as controls. The end point of clinical analysis was cancer recurrence. Average follow-up was 22.5 months. RESULTS: CEA mRNA was detected in all but four lymph nodes used as controls. All primary tumors were positive for CEA mRNA. Of 261 lymph nodes analyzed, 35 lymph nodes (13.4%) showed CEA mRNA levels higher than those detected in control lymph nodes and were considered positive for micrometastasis. Survival analysis by micrometastases showed less cancer recurrences in patients with lymph nodes negative for CEA mRNA (log rank, 5.3; p = 0.021). Among tumor type, tumor grading, age, sex, and molecularly detected lymph node micrometastases, the most powerful predictor of cancer recurrences was the presence of micrometastases (Cox proportional hazard, 3.3; p = 0.027). CONCLUSION: Quantitative real-time RT-PCR for CEA mRNA can be applied for detection of micrometastases in lymph nodes. This technique may be an appropriate tool in predicting cancer recurrences, and further studies are warranted to determine the most useful clinical applications.
STUDY OBJECTIVES: The survival of patients with surgically resected stage I non-small cell lung cancer (NSCLC) is not optimal, probably because of unsuspected systemic occult tumor dissemination. The current applied technologies and methods for scanning the body and examining lymph nodes for tumor cells have broadly recognized limitations. Several studies have reported that it is possible to detect occult lymph node metastases (micrometastases) using more sensitive methods such as immunohistochemistry or molecular technology. The aim of our study was to evaluate the utility of quantitative real-time reverse-transcriptase polymerase chain reaction (RT-PCR) for carcinoembryonic antigen (CEA) messenger RNA (mRNA) for detection of lymph node micrometastases and its impact on disease-free interval. METHODS: Quantitative real-time RT-PCR for CEA mRNA was performed on primary lung tumors and regional lymph nodes from 44 surgically resected NSCLCpatients classified as clinical stage I. Fourteen lymph nodes from five patients without malignancy were used as controls. The end point of clinical analysis was cancer recurrence. Average follow-up was 22.5 months. RESULTS:CEA mRNA was detected in all but four lymph nodes used as controls. All primary tumors were positive for CEA mRNA. Of 261 lymph nodes analyzed, 35 lymph nodes (13.4%) showed CEA mRNA levels higher than those detected in control lymph nodes and were considered positive for micrometastasis. Survival analysis by micrometastases showed less cancer recurrences in patients with lymph nodes negative for CEA mRNA (log rank, 5.3; p = 0.021). Among tumor type, tumor grading, age, sex, and molecularly detected lymph node micrometastases, the most powerful predictor of cancer recurrences was the presence of micrometastases (Cox proportional hazard, 3.3; p = 0.027). CONCLUSION: Quantitative real-time RT-PCR for CEA mRNA can be applied for detection of micrometastases in lymph nodes. This technique may be an appropriate tool in predicting cancer recurrences, and further studies are warranted to determine the most useful clinical applications.
Authors: Valentina Vaira; Alice Faversani; Nina M Martin; David S Garlick; Stefano Ferrero; Mario Nosotti; Joseph L Kissil; Silvano Bosari; Dario C Altieri Journal: Cancer Res Date: 2013-02-25 Impact factor: 12.701