Meta-Analysis:
A systematic review and meta-analysis of individual patient data on the impact of the BIM deletion polymorphism on treatment outcomes in epidermal growth factor receptor mutant lung cancer
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Abstract
Sheila X. Soh1,*, Fahad J. Siddiqui2,3,*, John C. Allen2, Go Woon Kim4, Jae Cheol Lee5, Yasushi Yatabe6, Manabu Soda7, Hiroyuki Mano7, Ross A. Soo8,9, Tan-Min Chin8,9, Hiromichi Ebi10, Seiji Yano10, Keitaro Matsuo11, Xiaomin Niu12, Shun Lu12, Kazutoshi Isobe13, Jih-Hsiang Lee14, James C. Yang15, Mingchuan Zhao16, Caicun Zhou16, June-Koo Lee17, Se-Hoon Lee18, Ji Yun Lee18, Myung-Ju Ahn18, Tira J. Tan19, Daniel S. Tan19, Eng-Huat Tan19, S. Tiong Ong1,19,20,21 and Wan-Teck Lim19
1Cancer and Stem Cell Biology Program, Duke-NUS Medical School, Singapore
2Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore
3Centre for Global Child Health, Sick Kids Hospital, Toronto, Canada
4Department of Pulmonary and Critical Care Medicine, Asan Medical Center, University of Ulsan, Seoul, Republic of Korea
5Department of Oncology, Asan Medical Center, University of Ulsan, Seoul, Republic of Korea
6Department of Pathology and Molecular Diagnostics, Aichi Cancer Center, Nagoya, Japan
7Department of Cellular Signaling, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
8Department of Haematology-Oncology, National University Cancer Institute, Singapore
9Cancer Science Institute, National University of Singapore, Singapore
10Division of Medical Oncology, Cancer Research Institute, Kanazawa University, Kanazawa, Japan
11Division of Molecular and Clinical Epidemiology, Aichi Cancer Center Research Institute, Nagoya, Japan
12Shanghai Lung Cancer Center, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China
13Department of Respiratory Medicine, Toho University Omori Medical Center, Tokyo, Japan
14Department of Medical Research, National Taiwan University Hospital, Taipei, Taiwan
15Department of Oncology, Graduate Institute of Oncology and Cancer Research Centre, National Taiwan University Hospital, Taipei, Taiwan
16Department of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China
17Department of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea
18Division of Hematology and Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
19Division of Medical Oncology, National Cancer Centre, Singapore
20Department of Haematology, Singapore General Hospital, Singapore
21Department of Medicine, Duke University Medical Center, Durham, North Carolina, USA
*These authors contributed equally to this work
Correspondence to:
Wan-Teck Lim, email: [email protected]
S. Tiong Ong, email: [email protected]
Keywords: BIM, polymorphism, tyrosine kinase inhibitor, lung cancer, drug resistance
Received: February 21, 2017 Accepted: March 30, 2017 Published: April 13, 2017
ABSTRACT
Background: A germline deletion in the BIM (BCL2L11) gene has been shown to impair the apoptotic response to tyrosine kinase inhibitors (TKIs) in vitro but its association with poor outcomes in TKI-treated non-small cell lung cancer (NSCLC) patients remains unclear. We conducted a systematic review and meta-analysis on both aggregate and individual patient data to address this issue.
Results: In an aggregate data meta-analysis (n = 1429), the BIM deletion was associated with inferior PFS (HR = 1.51, 95%CI = 1.06–2.13, P = 0.02). Using individual patient data (n = 1200), we found a significant interaction between the deletion and ethnicity. Amongst non-Koreans, the deletion was an independent predictor of shorter PFS (Chinese: HR = 1.607, 95%CI = 1.251–2.065, P = 0.0002; Japanese: HR = 2.636, 95%CI = 1.603–4.335, P = 0.0001), and OS (HR = 1.457, 95% CI = 1.063–1.997, P = 0.019). In Kaplan-Meier analyses, the BIM deletion was associated with shorter survival in non-Koreans (PFS: 8.0 months v 11.1 months, P < 0.0005; OS: 25.7 v 30.0 months, P = 0.042). In Koreans, the BIM deletion was not predictive of PFS or OS.
Materials and Methods: 10 published and 3 unpublished studies that reported survival outcomes in NSCLC patients stratified according to BIM deletion were identified from PubMed and Embase. Summary risk estimates were calculated from aggregate patient data using a random-effects model. For individual patient data, Kaplan-Meier analyses were supported by multivariate Cox regression to estimate hazard ratios (HRs) for PFS and OS.
Conclusions: In selected populations, the BIM deletion is a significant predictor of shorter PFS and OS on EGFR-TKIs. Further studies to determine its effect on response to other BIM-dependent therapeutic agents are needed, so that alternative treatment strategies may be devised.
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