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AI Biotech/Diagnostics: Cardio
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Application US20190018929
Published 2019-01-17
Predictive Test For Melanoma Patient Benefit From Interleukin-2 (il2) Therapy
A method is disclosed for predicting in advance whether a melanoma patient is likely to benefit from high dose IL2 therapy in treatment of the cancer. The method makes use of mass spectrometry data obtained from a blood-based sample of the patient and a computer configured as a classifier and making use of a reference set of mass spectral data obtained from a development set of blood-based samples from other melanoma patients. A variety of classifiers for making this prediction are disclosed, including a classifier developed from a set of blood-based samples obtained from melanoma patients treated with high dose IL2 as well as melanoma patients treated with an anti-PD-1 immunotherapy drug. The classifiers developed from anti-PD-1 and IL2 patient sample cohorts can also be used in combination to guide treatment of a melanoma patient.
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- 1. A method for detecting class labels in a melanoma patient, comprising the steps of:
a) performing mass spectrometry on a blood-based sample of the patient and obtaining mass spectrometry data of the sample; b) performing a classification of the mass spectrometry data with the aid of a computer implementing a classifier, wherein the classifier is developed from a development set of samples from melanoma patients treated with the high dose IL2 therapy and consists of a hierarchical combination of classifiers 1 and 2, wherein classifier 1 is developed from the development set of samples and a set of mass spectral features identified as being associated with an acute response biological function and generates either an Early class label and a Late class label, or the equivalent, and wherein classifier 2 is developed from a subset of samples in the development set classified as Late by classifier 1 and also generates an Early class label and a Late class label or the equivalent, wherein class labels are detected for the patient.
- 3. A method for detecting a class label in a melanoma, comprising the steps of:
a) performing mass spectrometry on a blood-based sample of the patient and obtaining mass spectrometry data of the sample; b) performing a classification of the mass spectrometry data with the aid of a computer implementing a classifier 2, wherein the classifier 2 is developed from a subset of a development set of samples from melanoma patients treated with the high dose IL2 therapy which have been classified as Late or the equivalent by a classifier 1 using a set of mass spectral features identified as being associated with an acute response biological function; wherein class labels are detected for the patient.
- 5. A classifier development method comprising the steps of:
a) obtaining a development set of blood-based samples from a population of melanoma patients in advance of treatment with high dose IL2 therapy; b) performing mass spectrometry on the development set of samples; c) with the aid of a computer developing a first classifier using a set of mass spectral features which are associated with an acute response biological function, the first classifier generating a class label of either early or late or the equivalent; d) classifying the development set of samples with the first classifier; e) selecting a subset of the samples which are classified as Late by the first classifier; f) with the aid of the computer, developing a second classifier using the subset selected in step e) as the development set of the second classifier, the second classifier generating a class label of early or late or the equivalent; and g) defining a final classification schema which combines the first classifier and the second classifier.
- 9. (canceled)
- 10. (canceled)
- 11. (canceled)
- 13. A method of detecting a class label for a melanoma patient on high dose IL2 therapy by performing a classification of the sample with a classifier developed from mass spectral data of a set of blood based samples obtained from melanoma patients treated with an anti-PD-1 drug, the classifier generating a class label of Late or the equivalent and Early or the equivalent, wherein a class label is detected.
- 14. A method of detecting a class label for a melanoma patient on high dose IL2 therapy by performing a classification of the sample with a hierarchical combination of tumor size classifiers developed from mass spectral data of a set of blood based samples obtained from melanoma patients treated with an anti-PD-1 drug, the hierarchical combination of tumor size classifiers generating a class label of either Good or the Equivalent or Bad or the equivalent, wherein a class label is detected.
