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Tailoring tyrosine kinase inhibitor therapy to tackle specific BCR-ABL1 mutant clones

  • Alfonso Quintás-Cardama(corresponding author)
    ,
*Corresponding author for this work
  • University of Texas Health Science Center at Houston
Scholary Output:
Contribution to journal
Article
Peer-review

Sustainable Development Goals

  • SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well

Abstract

Several tyrosine kinase inhibitors (TKIs) are currently under development for the treatment of patients with chronic myelogenous leukemia (CML) resistant or intolerant of imatinib therapy, including nilotinib, dasatinib, and bosutinib. The current paradigm of TKI therapy involves a sequential use of these compounds, with imatinib invariably used as frontline therapy followed by either dasatinib or nilotinib on an empiric basis. A more sensible approach to this sequence is the selection of the TKI best suited to overcome the resistance conferred by BCR-ABL1 mutations detected at each time-point. As more TKIs are becoming available, the management of patients with CML will require degree of "finesse" to better match each patient with the best TKI available. This match is best made based on available in vitro data regarding the activity of each agent against each specific mutation. The case herein reported supports such strategy.

Publication Information

Output type

Scholary Output:
Contribution to journal
Article
Peer-review

Original language

English (US)

Pages from-to (Number of pages)

Pages 1313-1316 (4 pages)

Journal (Volume, Issue Number)

Leukemia Research (Volume 32, Issue 8)

Publication milestones

  • Published - 08/2008

Publication status

Published - 08/2008

ISSN

0145-2126

Publication IDs

  • Scopus: 42749085070
  • PubMed: 18242697
  • ORCID: /0000-0002-8636-1071/work/68811102

Publication metrics

Metrics

Fractional count
1
Fractional count
0.50
Fractional count
1
Fractional count
0.50
Fractional count
1
Fractional count
1
SciVal
citations
9
Scopus
citations
SciVal
FWCI
0.65
SciVal
Author count
2
SciVal
Paper percentile
60

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Citation count
10
Captures
11

Funding Details

FunderFunding number
NCI
P30CA016672