Review: Precision medicine and driver mutations: Computational methods, functional assays and conformational principles for interpreting cancer drivers.
Journal
PLoS computational biology
ISSN: 1553-7358
Titre abrégé: PLoS Comput Biol
Pays: United States
ID NLM: 101238922
Informations de publication
Date de publication:
03 2019
03 2019
Historique:
entrez:
29
3
2019
pubmed:
29
3
2019
medline:
30
4
2019
Statut:
epublish
Résumé
At the root of the so-called precision medicine or precision oncology, which is our focus here, is the hypothesis that cancer treatment would be considerably better if therapies were guided by a tumor's genomic alterations. This hypothesis has sparked major initiatives focusing on whole-genome and/or exome sequencing, creation of large databases, and developing tools for their statistical analyses-all aspiring to identify actionable alterations, and thus molecular targets, in a patient. At the center of the massive amount of collected sequence data is their interpretations that largely rest on statistical analysis and phenotypic observations. Statistics is vital, because it guides identification of cancer-driving alterations. However, statistics of mutations do not identify a change in protein conformation; therefore, it may not define sufficiently accurate actionable mutations, neglecting those that are rare. Among the many thematic overviews of precision oncology, this review innovates by further comprehensively including precision pharmacology, and within this framework, articulating its protein structural landscape and consequences to cellular signaling pathways. It provides the underlying physicochemical basis, thereby also opening the door to a broader community.
Identifiants
pubmed: 30921324
doi: 10.1371/journal.pcbi.1006658
pii: PCOMPBIOL-D-18-01743
pmc: PMC6438456
doi:
Substances chimiques
Neoplasm Proteins
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, N.I.H., Intramural
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
e1006658Subventions
Organisme : NCI NIH HHS
ID : HHSN261200800001E
Pays : United States
Commentaires et corrections
Type : ErratumIn
Déclaration de conflit d'intérêts
The authors have declared that no competing interests exist.
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