[A diagnostic model of cerebrospinal protein fingerprint pattern for brain metastases of non-small cell lung cancer].

OBJECTIVE: To establish a diagnostic model of protein fingerprint pattern in the cerebrospinal fluid (CSF) for non-small-cell lung cancer (NSCLC) patients with brain metastases.
METHODS: The CSF samples were obtained from 29 NSCLC patients with brain metastasis, 23 non-tumor patients and 10 early-stage NSCLC patients without brain metastases for analysis of the protein expression profiles using surface-enhanced laser desorption/ionization-time of flight-mass spectrometry (SELDI-TOF-MS). The data were then analyzed by Biomarker Wizard software, and the tree analysis patterns were generated using the decision-tree model in Biomarker Patterns software. The diagnostic model was tested for its clinical application.
RESULTS: Five protein peaks were identified showing differential expression between patients with brain metastases and those without brain metastases. Combination of the 3 protein peaks (m/z: 8698.00, 1215.32 and 1245.70) could discriminate these two samples with a sensitivity of 100.00% (29/29) and a specificity of 100.00% (23/23). Five proteins were differentially expressed between the NSCLC patients with brain metastases and the non-tumor patients. With one protein peak (m/z: 6050.00), these two samples could be discriminated with a sensitivity of 90.00% (9/10) and a specificity of 78.26% (18/23).
CONCLUSION: The established diagnostic model of CSF protein fingerprint pattern provides high sensitivity and specificity in the diagnosis of NSCLC with brain metastasis.