A laboratory test processing center, comprising: one or more data storage devices storing (a) class-labeled mass spectral data obtained from blood-based samples of a multitude of cancer patients, the class labels for the mass spectral data indicating whether or not a patient associated with the mass spectral data benefitted from treatment of cancer from administration of an epidermal growth factor receptor pathway targeting drug; and (b) a mass spectrum of a blood-based sample of a cancer patient to be tested; a processing unit operating in accordance with a set of instructions to perform the following operations on the mass spectrum of the blood-based sample of a patient to be tested and the class-labeled mass spectral data: (a) perform one or more predefined pre-processing steps on the mass spectrum of the blood-based sample of a patient to be tested; (b) obtain integrated intensity values of features in the mass spectrum of the blood-based sample of a patient to be tested at one or more predetermined m/z ranges in said mass spectrum after the performance of said predefined pre-processing steps; c) implement a classification algorithm on the integrated intensity values and the class-labeled mass spectral data, the classification algorithm assigning a class label for the blood-based sample of a patient to be tested indicating whether or not the said patient is likely to benefit from administration of an epidermal growth factor receptor pathway targeting drug, wherein the class label is assigned by comparing the test spectrum generated from the patient sample with the class-labeled mass spectral data, and determining, based on the relation of the test spectrum to the group of class-labeled spectra, whether the patient will be responsive to said drug; and d) output the class label assigned by the classification algorithm to the blood-based sample of a cancer patient to be tested. one or more data storage devices storing (a) class-labeled mass spectral data obtained from blood-based samples of a multitude of cancer patients, the class labels for the mass spectral data indicating whether or not a patient associated with the mass spectral data benefitted from treatment of cancer from administration of an epidermal growth factor receptor pathway targeting drug; and (b) a mass spectrum of a blood-based sample of a cancer patient to be tested; a processing unit operating in accordance with a set of instructions to perform the following operations on the mass spectrum of the blood-based sample of a patient to be tested and the class-labeled mass spectral data: (a) perform one or more predefined pre-processing steps on the mass spectrum of the blood-based sample of a patient to be tested; (b) obtain integrated intensity values of features in the mass spectrum of the blood-based sample of a patient to be tested at one or more predetermined m/z ranges in said mass spectrum after the performance of said predefined pre-processing steps; c) implement a classification algorithm on the integrated intensity values and the class-labeled mass spectral data, the classification algorithm assigning a class label for the blood-based sample of a patient to be tested indicating whether or not the said patient is likely to benefit from administration of an epidermal growth factor receptor pathway targeting drug, wherein the class label is assigned by comparing the test spectrum generated from the patient sample with the class-labeled mass spectral data, and determining, based on the relation of the test spectrum to the group of class-labeled spectra, whether the patient will be responsive to said drug; and d) output the class label assigned by the classification algorithm to the blood-based sample of a cancer patient to be tested. (a) perform one or more predefined pre-processing steps on the mass spectrum of the blood-based sample of a patient to be tested; (b) obtain integrated intensity values of features in the mass spectrum of the blood-based sample of a patient to be tested at one or more predetermined m/z ranges in said mass spectrum after the performance of said predefined pre-processing steps; c) implement a classification algorithm on the integrated intensity values and the class-labeled mass spectral data, the classification algorithm assigning a class label for the blood-based sample of a patient to be tested indicating whether or not the said patient is likely to benefit from administration of an epidermal growth factor receptor pathway targeting drug, wherein the class label is assigned by comparing the test spectrum generated from the patient sample with the class-labeled mass spectral data, and determining, based on the relation of the test spectrum to the group of class-labeled spectra, whether the patient will be responsive to said drug; and d) output the class label assigned by the classification algorithm to the blood-based sample of a cancer patient to be tested.