Improving breast cancer subtypes diagnosis through bioinformatic analysis
2014
Northwestern University, Evanston, USA
In the present study, the researchers used computational techniques to analyze gene expression patterns from breast cancer patients data which are publically available from The Cancer Genome Atlas (TCGA). Novel signatures associated with transcription factor STAT3 (Signal transducer and activator of transcription 3) were identified and were shown to be specific for basal-like breast cancer and not seen in other subtypes such as luminal A or luminal B cancers. Because STAT3 is known to be important for basal-like breast cancer malignancy, elucidating its most highly affected downstream targets is of great importance to cancer diagnosis and therapy.
Bioinformatic analysis reveals a pattern of STAT3-associated gene expression specific to basal-like breast cancers in human tumors
Curt M. Horvath
Added on: 07-26-2021
[1] https://www.pnas.org/content/early/2014/08/19/1404881111[2] https://data.jrc.ec.europa.eu/dataset/352f7dfd-05cf-434b-a96a-7e270dc76573
