Genes associated with progression and response in chronic myeloid leukemia and uses thereof

• US 8,014,957 B2
• Filed: 12/14/2006
• Issued: 09/06/2011
• Est. Priority Date: 12/15/2005
• Status: Expired due to Fees

• Current Assignee: Fred Hutchinson Cancer Research Center (Fred Hutchinson Cancer Research Center|Argus Genetics|Mars), Rosetta Inpharmatics LLC (Merck & Co., Inc.)
• Original Assignee: Fred Hutchinson Cancer Research Center (Fred Hutchinson Cancer Research Center|Argus Genetics|Mars), Rosetta Inpharmatics LLC (Merck & Co., Inc.)
• Inventors: Dai, Hongyue, Radich, Jerald P., Schelter, Janell M., Linsley, Peter S., Mao, Mao
• Primary Examiner(s): Smith; Carolyn L.
• Application Number:
  US11/640,517
• Publication Number:
  US 20070154931A1
• Time in Patent Office: 1,727 Days
• Field of Search: None
• US Class Current: 702/19
• CPC Class Codes: C12Q 1/6886 for cancer immunoassay for cancer G01N33/574
• CPC Class Codes: C12Q 2600/106 Pharmacogenomics, i.e. genetic variability in individual responses to drugs and drug metabolism
• CPC Class Codes: C12Q 2600/112 Disease subtyping, staging or classification
• CPC Class Codes: C12Q 2600/136 Screening for pharmacological compounds
• CPC Class Codes: C12Q 2600/158 Expression markers
• CPC Class Codes: Y02A 90/10 Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Abstract

The invention provides molecular markers that are associated with the progression of chronic myeloid leukemia (CML), and methods and computer systems for monitoring the progression of CML in a patient based on measurements of these molecular markers. The present invention also provides CML target genes, and methods and compositions for treating CML patients by modulating the expression or activity of these CML target genes and/or their encoded proteins. The invention also provides genes that are associated with resistance to imatinib mesylate (Gleevec™) treatment in CML patients, and methods and compositions for determining the responsiveness of a CML patient to imatinib mesylate treatment based on measurements of these genes and/or their encoded proteins. The invention also provides methods and compositions for enhancing the effect of Gleevec™ by modulating the expression or activity of these genes and/or their encoded proteins.

Claims

1. A computer-implemented method for determining progression of chronic myeloid leukemia (CML) in a CML patient, comprising:

(a) classifying, on a computer, a marker profile comprising measurements of a plurality of gene products in a cell sample taken from said patient as a chronic phase (CP-CML) profile or as an advanced phase (ADV-CML) profile, wherein said gene products are respectively products of at least 5 of the genes listed in Table 1a;

(b) determining said patient as in a chronic phase if said marker profile is classified as a CP-CML profile, or determining said patient as in an advanced phase if said marker profile is classified as an ADV-CML profile; and

(c) outputting to a user, a user interface device, a monitor, a computer readable storage medium, a local computer, or a computer that is part of a network;

or displaying;

the determination resulting from step (b).

2. The method of claim 1, wherein said plurality of gene products further comprises a gene from Table 1b.

3. The method of claim 1, further comprising obtaining said marker profile by a method comprising measuring said plurality of gene products in a cell sample taken from said patient.

4. The method of claim 3, wherein said cell sample is a sample selected from the group consisting of bone marrow sample and peripheral blood sample.

5. The method of claim 1, wherein said classifying is carried out using a progression classifier, wherein said progression classifier receives an input comprising said marker profile and provides an output comprising data indicating whether said marker profile is a CP-CML profile or an ADV-CML profile.

6. The method of claim 5, wherein said step of classifying is carried out by a method comprising (i) comparing said marker profile with a CP-CML template profile and/or a ADV-CML said template profile, wherein said CP-CML template profile and/or said ADV-CML template profile is obtained from a training population comprising CML patients of the CP-CML and ADV-CML stage, respectively;

and (ii) classifying said marker profile as a CP-CML profile if said marker profile has a high similarity to said CP-CML template profile and/or has a low similarity to said ADV-CML template profile, or classifying said marker profile as a ADV-CML profile if said marker profile has a high similarity to said ADV-CML template profile and/or has a low similarity to said CP-CML template profile, wherein a high similarity corresponds to a degree of similarity above a predetermined threshold, and wherein a low similarity corresponds to a degree of similarity no greater than said predetermined threshold.

7. The method of claim 6, wherein said step of classifying is carried out by a method comprising (i) comparing said marker profile with said CP-CML template profile or said ADV-CML template profile;

and (ii) classifying said marker profile as a CP-CML profile if said marker profile has a high similarity to said CP-CML template profile or has a low similarity to said ADV-CML template profile, or classifying said marker profile as a ADV-CML profile if said marker profile has a high similarity to said ADV-CML template profile or has a low similarity to said CP-CML template profile, wherein a high similarity corresponds to a degree of similarity above a predetermined threshold, and wherein a low similarity corresponds to a degree of similarity no greater than said predetermined threshold.

8. The method of claim 6, wherein said step of classifying is carried out by a method comprising (i) comparing said marker profile with said CP-CML template profile and said ADV-CML template profile;

and (ii) classifying said marker profile as a CP-CML profile if said marker profile has a higher similarity to said CP-CML template profile than to said ADV-CML template profile, or classifying said marker profile as a ADV-CML profile if said marker profile has a higher similarity to said ADV-CML template profile than to said CP-CML template profile.

9. The method of claim 5, wherein said progression classifier is an artificial neural network (ANN) or a support vector machine (SVM).

10. The method of claim 1, wherein said gene products are products of at least 10 of the genes listed in Table 1a.

11. The method of claim 1, wherein said gene products further comprise products of at least 5 of the genes listed in Table 3.

12. The method of claim 11, wherein said gene products further comprise products of at least 5 up-regulated genes markers listed in Table 3, or are products of at least 5 down-regulated genes markers listed in Table 3.

13. The method of claim 1, wherein each of said gene products is a gene transcript.

14. The method of claim 13, wherein measurement of each said gene transcript is obtained by a method comprising contacting a positionally-addressable microarray with nucleic acids from said cell sample or nucleic acids derived therefrom under hybridization conditions, and detecting the amount of hybridization that occurs, said microarray comprising one or more polynucleotide probes complementary to a hybridizable sequence of each said gene transcript.

15. The method of claim 13, wherein measurement of each said gene transcript is obtained by quantitative reverse transcriptase PCR (qRT-PCR).

16. The method of claim 1, wherein each of said plurality of gene products is a protein.