Serum Protein Pattern Could Predict the Therapeutic Effect of First-Line Pemetrexed/Cisplatin Chemotherapy in Patients With Lung Adenocarcinoma

Hong Shen, Xue-Feng Fang, Ying Yuan, Jiao Yang, Shu Zheng


Background: In patients with advanced non-squamous non-small cell lung cancer (NSCLC), a pemetrexed/cisplatin (PP) regimen is considered as one of the preferred first-line treatments. However, only about half of the treated patients respond, and there is no clinically useful marker that can predict the response to the regimen.

Methods: We established a potential pattern for the prediction of efficacy of first-line PP chemotherapy in patients with lung adenocarcinoma, by using artificial neural networks (ANNs) analysis of surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) in this preliminary study.

Results: The samples were randomly divided into training set and test set. From the test set, through cross-validation, the established protein pattern for PP separated the responders from the non-responders with a sensitivity of 95.8% and a specificity of 90.0%.

Conclusion: It could be helpful for oncologists to select patients who could benefit from PP chemotherapy.

World J Oncol. 2015;6(1):292-296


Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry; Artificial neural networks; Non-small cell lung cancer; Chemotherapy; Protein pattern; Adenocarcinoma

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