Plasma metabolomic profiling to predict durable response and survival with afatinib in EGFR-mutated non-small cell lung cancer: A prospective, multicenter, observational biomarker study
Takeshi Honda, Kei Morikawa, Saori Takata, Hisashi Tanaka, Hidetoshi Itani, Kazuya Horiuchi, Ichiro Kawada, Hideyuki Nakagawa, Yoshiro Nakahara, Yoshitaka Seki, Akihiro Bessho, Nobumasa Takahashi, Kentaro Hayashi, Takeo Endo, Kiyoshi Takeyama, Toshiya Maekura, Nagio Takigawa, Akikazu Kawase, Makoto Endoh, Kenji Nemoto, Kazuma Kishi, Tomoko Fukuuchi, Yuko Iwasaki, Kenzo Soejima, Yusuke Okuma, Akira Togashi, Koji Ueda, Kenichi Yoshimura, Noriyuki Matsutani, Nobuhiko Seki, Daisuke SaigusaBackground
While EGFR tyrosine kinase inhibitors (TKIs) like afatinib are standard treatments for EGFR-mutated non-small cell lung cancer (NSCLC), predicting which patients will achieve durable responses remains challenging. Given the emergence of more toxic and costly combination therapies, identifying candidates who can achieve long-term survival with TKI monotherapy is a critical clinical priority.
Objectives
To identify baseline plasma and extracellular vesicle (EV) metabolomic biomarkers that predict progression-free survival (PFS) and overall survival (OS) in patients treated with first-line afatinib.
Design
A prospective, multicenter, single-arm observational biomarker discovery study (the EXTRA study).
Methods
We enrolled 103 patients with advanced or recurrent EGFR-mutated NSCLC. Fasting plasma (n = 101 evaluable) and EV (n = 99 evaluable) samples collected at baseline were subjected to comprehensive metabolomic profiling (630 metabolites) using the MxP® Quant 500 kit (Biocrates Life Sciences AG, Innsbruck, Austria) combined with UHPLC-MS/MS. Durable response was defined as a progression-free survival (PFS) of 18 months or longer. Associations with PFS and OS were evaluated using false discovery rate (FDR)-adjusted univariable Cox models and validated via bootstrap resampling.
Results
In this first large-scale concurrent analysis, baseline EV metabolites unexpectedly showed no significant correlation with survival end points. Conversely, baseline plasma metabolites provided robust predictive signatures. Histidine and five lysophosphatidylcholines (LPC16:0, 17:0, 18:0, 18:1, 18:2) were identified as significant positive predictors of PFS. For OS, one phosphatidylcholine (PC ae C30:1) and four amino acids (homoarginine, histidine, threonine, tryptophan) were positive predictors, while one dihydroceramide (Cer [d18:1/24:1]) was a negative predictor. Prognostic scores based on these metabolites successfully stratified patients into three risk groups with significantly distinct survival outcomes (p < 0.001).
Conclusion
Plasma-derived, but not EV-derived, metabolomic signatures accurately predict durable response and survival in EGFR-mutated NSCLC treated with afatinib. These novel biomarkers reflect host immunity and tumor microenvironment states, offering a step toward precision medicine by identifying patients likely to benefit from monotherapy over intensive combination regimens.
Registration
University Hospital Medical Information Network Clinical Trials Registry (UMIN-CTR),