Publication: Deciphering the signaling network of breast cancer improves drug sensitivity prediction
Deciphering the signaling network of breast cancer improves drug sensitivity prediction
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Tognetti, M., Gabor, A., Yang, M., Cappelletti, V., Windhager, J., Rueda, O. M., Charmpi, K., Esmaeilishirazifard, E., Bruna, A., de Souza, N., Caldas, C., Beyer, A., Picotti, P., Saez-Rodriguez, J., & Bodenmiller, B. (2021). Deciphering the signaling network of breast cancer improves drug sensitivity prediction. Cell Systems, 12(5), 401-418.e12. https://doi.org/10.1016/j.cels.2021.04.002
Abstract
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Abstract
One goal of precision medicine is to tailor effective treatments to patients' specific molecular markers of disease. Here, we used mass cytometry to characterize the single-cell signaling landscapes of 62 breast cancer cell lines and five lines from healthy tissue. We quantified 34 markers in each cell line upon stimulation by the growth factor EGF in the presence or absence of five kinase inhibitors. These data-on more than 80 million single cells from 4,000 conditions-were used to fit mechanistic signaling network models that provid
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- Tognetti, Marco
- Gabor, Attila
- Yang, Mi
- Cappelletti, Valentina
- Windhager, Jonas
- Rueda, Oscar M
- Charmpi, Konstantina
- Esmaeilishirazifard, Elham
- Bruna, Alejandra
- de Souza, Natalie
- Caldas, Carlos
- Beyer, Andreas
- Picotti, Paola
- Saez-Rodriguez, Julio
- Bodenmiller, Bernd
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Tognetti, M., Gabor, A., Yang, M., Cappelletti, V., Windhager, J., Rueda, O. M., Charmpi, K., Esmaeilishirazifard, E., Bruna, A., de Souza, N., Caldas, C., Beyer, A., Picotti, P., Saez-Rodriguez, J., & Bodenmiller, B. (2021). Deciphering the signaling network of breast cancer improves drug sensitivity prediction. Cell Systems, 12(5), 401-418.e12. https://doi.org/10.1016/j.cels.2021.04.002
