TY  -  
T1  - Network-guided identification of cancer-selective combinatorial therapies in ovarian cancer 
SN  -  /  
UR  - http://hdl.handle.net/10138/337782 
T3  -  
A1  - He, Liye; Bulanova, Daria; Oikkonen, Jaana; Häkkinen, Antti; Zhang, Kaiyang; Zheng, Shuyu; Wang, Wenyu; Erkan, Erdogan Pekcan; Carpén, Olli; Joutsiniemi, Titta; Hietanen, Sakari; Hynninen, Johanna; Huhtinen, Kaisa; Hautaniemi, Sampsa; Vähärautio, Anna; Tang, Jing; Wennerberg, Krister; Aittokallio, Tero 
A2  -  
PB  -  
Y1  - 2021 
LA  - eng 
AB  - Each patient’s cancer consists of multiple cell subpopulations that are inherently heterogeneous and may develop differing phenotypes such as drug sensitivity or resistance. A personalized treatment regimen should therefore target multiple oncoproteins in the cancer cell populations that are driving the treatment resistance or disease progression in a given patient to provide maximal therapeutic effect, while avoiding severe co-inhibition of non-malignant cells that would lead to toxic side effe... 
VO  -  
IS  -  
SP  -  
OP  -  
KW  - 3122 Cancers; toxic effects; combination synergy; ovarian cancer; network visualization; precision oncology; machine learning; drug combinations; DRUG; MODELS 
N1  -   
PP  -  
ER  -