Treatment selection for lung cancer patients using mass spectrum of blood-based sample

摘要

A test for predicting whether a non-small-cell lung cancer patient is more likely to benefit from an EGFR-I as compared to chemotherapy uses a computer-implemented classifier operating on a mass spectrum of a blood-based sample obtained from the patient. The classifier makes use of a training set which includes mass spectral data from blood-based samples of other cancer patients who are members of a class of patients predicted to have overall survival benefit on EGFRI-Is, e.g., those patients testing VS Good under the test described in U.S. Pat. No. 7,736,905. This class-labeled group is further subdivided into two subsets, i.e., those patients which exhibited early (class label “early”) and late (class label “late”) progression of disease after administration of the EGFR-I in treatment of cancer.

主权项

1. A method for predicting in advance whether a non-small-cell lung cancer (NSCLC) patient is a member of a class of cancer patients likely to obtain greater benefit from a treatment for the NSCLC in the form of administration of an epidermal growth factor receptor inhibitor (EGFR-I) as compared to chemotherapy, comprising the steps of:
(a) storing in a computer readable medium a training set comprising class-labeled mass spectral data obtained from a multitude of cancer patients who are determined by mass spectrometry of a blood-based sample to be members of a class of patients that are predicted to obtain overall survival benefit from an EGFR-I in treatment of the cancer, such class of patients further divided into two sub-classes:
1) those patients which exhibited early progression of disease after administration of the EGFR-I in treatment of cancer, mass spectral data of such patients having a class label of “early” or the equivalent; and2) those patients which exhibited late progression of disease after administration of an EGFR-I in treatment of cancer, mass spectral data of such patients having a class label of “late” or the equivalent; (b) providing a blood-based sample from the NSCLC patient to a mass spectrometer and conducting mass spectrometry on the blood-based sample and thereby generating a mass spectrum for the blood-based sample; (c) conducting pre-defined pre-processing steps on the mass spectrum obtained in step b) with the aid of a programmed computer; (d) obtaining integrated intensity feature values of selected features in said mass spectrum at a plurality of predefined m/z ranges after the pre-processing steps on the mass spectrum recited in step c) have been performed; and (e) executing in the programmed computer a classifier including a classification algorithm comparing the integrated intensity values obtained in step (d) with the training set stored in step (a) and responsively generating a class label for the blood-based sample, wherein if the class label generated in step (e) is “late” or the equivalent for the mass spectrum of the blood based sample, the patient is identified as being likely to obtain greater benefit from the EGFR-I as compared to chemotherapy in treatment of the cancer.