To this end, dataset GSE2740 was downloaded from GEO. This dataset includes samples from 4 platforms selleck bio and various breast cancer subtypes. To avoid possible bias due to platforms and breast cancer subtypes, only patient samples of Lumina A sub type and from the platform with the largest sample size were chosen. A total of 97 breast cancer patients microarray data samples were tested against our BRCA MoNet using the reverse prediction. The ranking result is shown in Figure 3 A. Particular, several BRCA MoAs were consistently ranked at the top, where BRCA MoA24 ranked the first in 30. 21% of the all the patients and ranked above top 20 in 61. 46% of all the patients among all 109 BRCA MoAs. BRCA MoA24 includes five drugs spironolactone, rifabutin, vorinostat, tri chostatin A and CP 690334 01.

Among these five drugs, spironolactone is a synthetic, steroidal anti mineralocorti coid agent with anti androgen, weak pro gestogen proper ties, and indirect estrogen effects. It has been used to reduce the elevated or unwanted androgen activity in the body. So, spironolactone can be potentially used to induce anti estrogenic activity against breast cancer. Rifabutin is a semisynthetic ansamycin and primarily used in the treatment of tuberculosis. Interestingly, ansamycin has been found to be a HSP90 inhibitor and many of its synthetic compounds are on trials as anti breast cancer drug. Vorinostat is a member of a histone deacety lases with a broad spectrum of epigenetic activ ities. it has been approved by the FDA to treat cutaneous T cell lymphoma in 2006.

Since it has been also shown to have effect on treating breast cancer, it has under gone multiple Phase I and II clinical trials as an anti breast cancer drug. Trichostatin A is an organic compound that serves as an antifungal antibiotic and selec tively inhibits class I and II mammalian HADC families of enzymes. It has gained extremely high attention in recent years and has been actively studied for its potent antitumor activity against breast cancer ever since 2001. Although the information of the last drug is not available, the overrepresentation of breast cancer related drugs in this MoA gives us a clear vision of the significant detection power of BRCA MoNet when applied to real patient data. Conclusion A drug effect MoA network for breast cancer cell lines, BRCA MoNet, was constructed by using the cMap expres sion data.

Batimastat It was developed selleck chemicals to address the problems of the cMap algorithm and to provide robustness and more accurate predictions for treatment effectiveness prediction and drug screening. This improvement came partially as a result of careful quality control on cMap data. In contrast to cMap, BRCA MoNet prediction is cell line specific and removes the burden for user to select an effect signature gene set.