Potential predictive value of serum targeted metabolites and concurrently mutated genes for EGFR-TKI therapeutic efficacy in lung adenocarcinoma patients with EGFR sensitizing mutations.

There is a discrepancy in the efficacy of epidermal growth factor receptor-tyrosine kinase inhibitor (EGFR-TKI) treatment for advanced lung adenocarcinoma (LUAD) patients with EGFR sensitizing mutations (mEGFR). Molecular markers other than mEGFR remain to be investigated to better predict EGFR-TKI efficacy. Here, 49 LUAD patients with mEGFR (19 deletions or 21 L858R mutations) who received the first-generation EGFR-TKI icotinib therapy were included and stratified into 25 good-responders with a progression-free survival (PFS) longer than 11 months and 24 poor-responders with a PFS shorter than 11 months. We conducted targeted metabolomic detection and next-generation sequencing on serum and tissue samples, respectively. Subsequently, two metabolomic profiling-based discriminant models were constructed for icotinib efficacy prediction, 10 metabolites overlapped in both models ensured high credibility for distinguishing good- and poor-responders. Seven of the 10 metabolites displayed significant differences between the two groups, which belong to lipids including ceramides (Cers), lysophosphatidylcholines (LPCs), lysophosphatidylethanolamines (LPEs), sphingomyelins (SMs), and free fatty acids (FAs). Briefly, LPC 16:1, LPC 22:5-1, and LPE 18:2 decreased in poor-responders, while Cer 36:1-3, Cer 38:1-3, SM 36:1-2 and SM 42:2 increased in poor-responders. In parallel, we identified 6 co-mutated genes (ARID1A, ARID1B, BCR, FANCD2, PTCH1, and RBM10) which were significantly correlated with a shorter PFS. Additionally, 4 efficacy-related metabolites (Cer 36:1-3, Cer 38:1-3, SM 36:1-2, and LPC 16:1) showed significant differences between the mutant and wild-type of 4 efficacy-related genes (ARID1A, ARID1B, BCR, and RBM10). SM 36:1-2 elevated while LPC 16:1 decreased in ARID1A, BCR, and RBM10 mutant groups compared to the wild-type groups. Cer 36:1-3 increased in the ARID1A and BCR mutant groups, and Cer 38:1-3 only rose in the ARID1A mutant group. Furthermore, we observed a causal-mediator-network-based interrelation between the 4 concurrently mutated genes and the 4 metabolites related metabolic genes in glycerophospholipid metabolism and sphingolipid metabolism pathways. This study demonstrated that lipids metabolism and concurrently mutated genes with mEGFR were associated with the icotinib efficacy, which provides novel perspectives in classifying clinical responses of mEGFR LUAD patients and reveals the potential of non-invasive pretreatment serum metabolites in predicting EGFR-TKI efficacy. AJCR