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

Pagination

1010-1018

Auteurs

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Classifications MeSH