232 - Nested case control study of proteomic biomarkers for interstitial lung disease in japanese patients with non-small cell lung cancer treated with er...

Date 28 September 2012
Event ESMO Congress 2012
Session Publication Only
Topics Complications/Toxicities of Treatment
Thoracic Malignancies
Translational Research
Basic Principles in the Management and Treatment (of cancer)
Presenter Nobuyuki Katakami
Authors N. Katakami1, S. Atagi2, H. Yoshioka3, M. Fukuoka4, A. Ogiwara5, M. Imai6, M. Ueda7, S. Matsui8
  • 1Division Of Integrated Oncology, Institute of Biomedical Research & Innovation Hospital, 650-0047 - Kobe/JP
  • 2Internal Medicine, National Hospital Organization Kinki-Chuo Chest Medical Center, Sakai/JP
  • 3Respiratory Medicine Dept., Kurashiki Central Hospital, Kurashiki/JP
  • 4Medical Oncology, Izumi Municipal HospitalCancer Center, JP-589-8511 - Izumi City/JP
  • 5Research And Development, Medical ProteoScope Co., Ltd, Yokohama/JP
  • 6Primary Lifecycle Management, Chugai Pharmaceutical Co., Ltd, Tokyo/JP
  • 7Clinical Research Planning, Chugai Pharmaceutical Co., Ltd, Tokyo/JP
  • 8Data Science, The Institute of Statistical Mathematics, Tachikawa/JP



Interstitial lung disease (ILD) is a serious adverse drug reaction associated with EGFR tyrosine kinase inhibitors, but its risk factors are yet to be elucidated. We sought to identify the proteomic biomarkers associated with ILD in Japanese patients with non-small cell lung cancer treated with erlotinib, and to build predictive models for development of ILD using the proteomic biomarkers.


We conducted a nested case control study. The cases were subjects in whom ILD developed within 120 days after the administration of erlotinib following enrolment in the cohort, and the controls were randomly selected from patients without ILD who were treated with erlotinib. For the proteomics analysis, albumin and IgG were removed from serum samples obtained before the first administration of erlotinib, then the samples were digested with protease and the resultant peptide fragments were separated, identified and assayed by LC–MS/MS. Logistic regression analysis was used for the identification and examination of predictability for ILD.


A total of 645 patients were enrolled in the cohort, 15 cases and 64 controls were analysed. Logistic regression analysis was performed to identify the peptide peaks and proteins assossiated with ILD. When multiplicity was taken into account, we were unable to statistically verify any genuine association between individual markers and ILD. Investigation of the predictive power based on leave-one-out cross-validation showed that the area under the ROC curve was 0.73 at a maximum. However, additional analysis suggested that three proteins (C3, C4A/C4B and APOA1) have a stronger association with ILD than the other proteins tested.


We were unable to conclude from the results of this study that any promising serum protein markers for predicting ILD had been identified. However, C3, C4A/C4B and APOA1 were suggested to be worth further investigation.


N. Katakami: corporate-sponsored research (Chugai Pharmaceutical Company).

S. Atagi: corporate-sponsored research (Chugai Pharmaceutical Company).

H. Yoshioka: corporate-sponsored research (Chugai Pharmaceutical Company).

M. Fukuoka: other substantive relationships (Chugai, Astra Zeneca).

A. Ogiwara: corporate-sponsored research (Chugai, Astra Zeneka).

M. Imai: M Imai is employee of Chugai Pharmaceutical Co., Ltd.

M. Ueda: M Ueda is employee of Chugai Pharmaceutical Co., Ltd.

All other authors have declared no conflicts of interest.