Individualized systems medicine strategy to tailor treatments for patients with chemorefractory acute myeloid leukemia

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

  • Tea Pemovska
  • Mika Kontro
  • Bhagwan Yadav
  • Henrik Edgren
  • Samuli Eldfors
  • Agnieszka Szwajda
  • Henrikki Almusa
  • Maxim M Bespalov
  • Pekka Ellonen
  • Erkki Elonen
  • Bjørn T Gjertsen
  • Riikka Karjalainen
  • Evgeny Kulesskiy
  • Sonja Lagström
  • Anna Lehto
  • Maija Lepistö
  • Tuija Lundán
  • Muntasir Mamun Majumder
  • Jesus M Lopez Marti
  • Pirkko Mattila
  • Astrid Murumägi
  • Satu Mustjoki
  • Aino Palva
  • Alun Parsons
  • Tero Pirttinen
  • Maria E Rämet
  • Minna Suvela
  • Laura Turunen
  • Imre Västrik
  • Maija Wolf
  • Jonathan Knowles
  • Tero Aittokallio
  • Caroline A Heckman
  • Kimmo Porkka
  • Olli Kallioniemi

UNLABELLED: We present an individualized systems medicine (ISM) approach to optimize cancer drug therapies one patient at a time. ISM is based on (i) molecular profiling and ex vivo drug sensitivity and resistance testing (DSRT) of patients' cancer cells to 187 oncology drugs, (ii) clinical implementation of therapies predicted to be effective, and (iii) studying consecutive samples from the treated patients to understand the basis of resistance. Here, application of ISM to 28 samples from patients with acute myeloid leukemia (AML) uncovered five major taxonomic drug-response subtypes based on DSRT profiles, some with distinct genomic features (e.g., MLL gene fusions in subgroup IV and FLT3-ITD mutations in subgroup V). Therapy based on DSRT resulted in several clinical responses. After progression under DSRT-guided therapies, AML cells displayed significant clonal evolution and novel genomic changes potentially explaining resistance, whereas ex vivo DSRT data showed resistance to the clinically applied drugs and new vulnerabilities to previously ineffective drugs.

SIGNIFICANCE: Here, we demonstrate an ISM strategy to optimize safe and effective personalized cancer therapies for individual patients as well as to understand and predict disease evolution and the next line of therapy. This approach could facilitate systematic drug repositioning of approved targeted drugs as well as help to prioritize and de-risk emerging drugs for clinical testing.

OriginalsprogEngelsk
TidsskriftCancer Discovery
Vol/bind3
Udgave nummer12
Sider (fra-til)1416-29
Antal sider14
ISSN2159-8274
DOI
StatusUdgivet - dec. 2013
Eksternt udgivetJa

ID: 199431639