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Acquired Resistance to Alectinib in ALK-Rearranged Lung Cancer due to ABCC11/MRP8 Overexpression in a Clinically Paired Resistance Model.

Tomoko FunazoTakahiro TsujiHiroaki OzasaKoh FurugakiYasushi YoshimuraTetsuya OguriHitomi AjimizuYuto YasudaTakashi NomizoYuichi SakamoriHironori YoshidaYoung Hak KimToyohiro Hirai
Published in: Molecular cancer therapeutics (2020)
Alectinib is used as a first-line treatment for anaplastic lymphoma kinase (ALK)-rearranged non-small cell lung cancer (NSCLC). Whereas other ALK inhibitors have been reported to be involved in resistance to ATP-binding cassette (ABC) transporters, no data are available regarding the association between resistance to alectinib and ABC-transporters. To investigate whether ABC-transporters contribute to alectinib resistance, ABC-transporter expression in alectinib-resistant cell lines derived from a patient with ALK-rearranged NSCLC and from H2228 lung cancer cells was evaluated and compared with that in each parent cell type. ATP-binding cassette subfamily C member 11 (ABCC11) expression was significantly increased in alectinib-resistant cell lines compared with that in alectinib-sensitive lines. ABCC11 inhibition increased sensitivity to alectinib in vitro ABCC11-overexpressing cells were established by transfection of an ABCC11 expression vector into H2228 cells, while control cells were established by transfecting H2228 cells with an empty vector. ABCC11-overexpressing cells exhibited decreased sensitivity to alectinib compared with that of control cells in vitro Moreover, the tumor growth rate following alectinib treatment was higher in ABCC11-overexpressing cells than that in control cells in vivo In addition, the intracellular alectinib concentration following exposure to 100 nmol/L alectinib was significantly lower in the ABCC11-overexpressing cell line compared with that in control cells. This is the first preclinical evidence showing that ABCC11 expression may be involved in acquired resistance to alectinib.
Keyphrases
  • induced apoptosis
  • cell cycle arrest
  • endoplasmic reticulum stress
  • poor prognosis
  • signaling pathway
  • machine learning
  • oxidative stress
  • transcription factor
  • bone marrow
  • pi k akt
  • tyrosine kinase
  • deep learning