In Silico Design and Experimental Validation of Combination Therapy for Pancreatic Cancer.
Journal
IEEE/ACM transactions on computational biology and bioinformatics
ISSN: 1557-9964
Titre abrégé: IEEE/ACM Trans Comput Biol Bioinform
Pays: United States
ID NLM: 101196755
Informations de publication
Date de publication:
Historique:
pubmed:
4
10
2018
medline:
27
4
2021
entrez:
4
10
2018
Statut:
ppublish
Résumé
The number of deaths associated with Pancreatic Cancer has been on the rise in the United States making it an especially dreaded disease. The overall prognosis for pancreatic cancer patients continues to be grim because of the complexity of the disease at the molecular level involving the potential activation/inactivation of several diverse signaling pathways. In this paper, we first model the aberrant signaling in pancreatic cancer using a multi-fault Boolean Network. Thereafter, we theoretically evaluate the efficacy of different drug combinations by simulating this boolean network with drugs at the relevant intervention points and arrive at the most effective drug(s) to achieve cell death. The simulation results indicate that drug combinations containing Cryptotanshinone, a traditional Chinese herb derivative, result in considerably enhanced cell death. These in silico results are validated using wet lab experiments we carried out on Human Pancreatic Cancer (HPAC) cell lines.
Identifiants
pubmed: 30281473
doi: 10.1109/TCBB.2018.2872573
doi:
Substances chimiques
Antineoplastic Agents
0
Phenanthrenes
0
cryptotanshinone
5E9SXT166N
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM