METHOD FOR TREATING AND IDENTIFYING LUNG CANCER PATIENTS LIKELY TO BENEFIT FROM EGFR INHIBITOR AND A MONOCLONAL ANTIBODY HGF INHIBITOR COMBINATION THERAPY
A test to identify whether a lung patient is likely to benefit from combination therapy in the form of an epidermal growth factor receptor inhibitor (EGFR-I) and a monoclonal antibody drug targeting hepatocyte growth factor (HGF) as compared to EGFR-I monotherapy. The test makes use of a mass spectrum obtained from a serum or plasma sample and a computer configured as a classifier operating on the mass spectrum and a training set in the form of class-labeled mass spectra from other cancer patients. The computer classifier executes a classification algorithm, such as K-nearest neighbor, and assigns a class label to the serum or plasma sample. Samples classified as “Poor” or the equivalent are associated with patients which are likely to benefit from the combination therapy more than from EGFR-I monotherapy. The invention also includes improved methods of treating patients predicted by the test.本發明提供一種鑑別肺臟病患是否相比於EGFR-I單藥療法,可能受益於採用表皮生長因子受體抑制劑(EGFR-I)及靶向肝細胞生長因子(HGF)之單株抗體藥物形式之組合療法之測試。該測試利用獲自血清或血漿樣品之質譜及電腦,其組態為對該質譜及來自其他癌症病患的類別標記質譜形式的訓練集進行操作之分類器。該電腦分類器執行分類算法,諸如K-最近鄰算法,且向該血清或血漿樣品分配類別標記。分類為「不佳」或其同義字之樣品將與相比於EGFR-I單藥療法,可能更受益於該組合療法之病患相關。本發明亦包括治療該測試所預測病患之改良方法。
