Methods and compositions for detection of breast cancer
View Patent ↗Systematic comparisons of breast ductal fluid samples obtained by nipple aspiration from women with unilateral breast cancer revealed significant differences in ductal fluid protein expression between the breast with cancer and the breast without cancer in each patient. This study demonstrates that breast ductal fluid contains over 1000 separate protein species and suggests that ductal fluids from breast cancer patients may be useful for high-throughput biomarker discovery.
1. A method for identifying a marker for breast cancer comprising:
a) collecting a first sample comprising nipple aspiration fluid from a cancerous breast of a cancer patient;
b) collecting a second sample comprising nipple aspiration fluid from a noncancerous breast of the cancer patient, wherein the first and second samples comprising fluid from cancerous and noncancerous breasts of the same cancer patient constitutes a paired sample;
c) separating breast fluid proteins within each of the samples by two-dimensional gel electrophoresis and forming profiles of the separated breast fluid proteins; and,
d) comparing the profiles of breast fluid proteins from the first and second samples,
wherein a difference in the profiles identifies a breast cancer marker.
2. The method of claim 1 , further comprising staining the breast fluid proteins.
3. The method of claim 2 , wherein the protein staining comprises exposing the gel to silver staining, fluorescent staining, or a colorimetric dye.
4. The method of claim 3 , wherein the colorimetric dye comprises coomassie blue or ruby red.
5. The method of claim 1 , further comprising generating a computer-assisted image of the profiles prior to comparing the profiles.
6. The method of claim 5 , wherein a learning algorithm is employed to compare the computer-assisted images of the profiles.
7. The method of claim 6 , wherein the learning algorithm is a trained support vector machine.
8. The method of claim 5 , further comprising providing the computer assisted images of the profiles to a trained support vector machine.
9. The method of claim 1 , further comprising collecting paired samples from additional cancer patients, and repeating steps (c-d) with the paired samples from the additional cancer patients, wherein the profiles of the paired samples identifies a pattern of breast proteins in which a breast cancer marker is identified.
10. The method of claim 9 , wherein multiple breast cancer markers are identified from the pattern of breast proteins.
11. A method of detecting development or progression of breast cancer in a patient comprising:
a) collecting a sample comprising nipple aspiration fluid from at least one breast of the patient;
b) separating breast fluid proteins in the sample by two-dimensional gel electrophoresis; and,
c) analyzing a breast fluid protein profile from the sample to detect a breast cancer marker identified byte method of claim 9 .
12. A method of detecting development or progression of breast cancer in a patient comprising:
a) collecting a sample comprising nipple aspiration fluid from at least one breast of the patient;
b) assaying the sample for a breast cancer marker identified by the method of claim 9 .
13. The method of claim 1 , wherein nipple aspiration fluid is collected from the cancerous and noncancerous breasts of the patient using a mild suction device.
14. A method of identifying a breast cancer marker comprising:
a) collecting a first sample comprising nipple aspiration fluid from a cancerous breast of a cancer patient;
b) collecting a second sample comprising nipple aspiration fluid from a noncancerous breast of the cancer patient, wherein the first and second samples comprising fluid from the cancerous and noncancerous breasts of the same cancer patient constitutes a paired sample;
c) separating breast fluid proteins within each of the samples by two-dimensional gel electrophoresis and fanning profiles of the separated breast fluid proteins; and,
d) comparing the profiles of breast fluid proteins from the first and second samples,
wherein a difference in the profiles identifies a breast cancer marker.
15. The method of claim 14 , further comprising staining the breast fluid proteins.
16. The method of claim 15 , wherein the protein staining comprises exposing the gel to silver staining, fluorescent staining, or a colorimetric dye.
17. The method of claim 16 , wherein the colorimetric dye comprises coomassie blue or ruby red.
18. The method of claim 14 , further comprising generating a computer-assisted image of the profiles prior to comparing the profiles.
19. The method of claim 18 , wherein a learning algorithm is employed to compare the computer-assisted images of the profiles.
20. The method of claim 19 , wherein the learning algorithm is a trained support vector machine.
21. The method of claim 18 , further comprising providing the computer assisted images of the profiles to a trained support vector machine.
22. A method of identifying a marker for breast cancer in a patient comprising:
a) collecting a blood serum sample from a breast cancer patient;
b) collecting a nipple aspiration fluid sample from a cancerous breast of the breast cancer patient;
c) separating blood serum proteins in the blood serum sample and breast fluid proteins in the nipple aspiration fluid sample by two-dimensional polyacrylamide gel electrophoresis and forming profiles of the separated proteins and,
d) comparing a blood serum protein profile from step c) with a breast fluid protein profile from step c),
wherein a difference in the profiles identifies a breast cancer marker.
23. The method of claim 22 , further comprising stain ink the blood serum proteins and the breast fluid proteins.
24. The method of claim 23 , wherein protein staining comprises exposing the gel to silver staining, fluorescent staining, or a calorimetric dye.
25. The method of claim 24 , wherein the calorimetric dye comprises coomassie blue or ruby red.
26. The method of claim 22 , further comprising generating a computer-assisted image of the profiles prior to comparing the profiles.
27. The method of claim 26 , wherein a learning algorithm is employed to compare the computer-assisted images of the profiles.
28. The method of claim 27 , wherein the learning algorithm is a trained support vector machine.
29. The method of claim 26 , further comprising providing the computer assisted images of the profiles to a trained support vector machine.