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Evaluating for Correlations between Specific Metabolites in Patients Receiving First-Line or Second-Line
Yanjun Xu1, Kaibo Ding1, Zhongsheng Peng1
1Department of Medical Thoracic Oncology, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, China.
Abstract:
Immune checkpoint inhibitors (ICI) have displayed impressive clinical efficacy in the context of non-small cell lung cancer (NSCLC). However, most patients do not achieve long-term survival. Minimally invasive collected samples are attracting significant interest as new fields of biomarker study, and metabolomics is one of these growing fields. We concentrated on the augmented value of the metabolomic profile in differentiating long-term survival from short-term survival in patients with NSCLC subjected to ICIs. We prospectively recruited 97 patients with stage IV NSCLC who were treated with anti-PD-1 inhibitor, including patients treated with monoimmunotherapy as second-line treatment (Cohort 1), and patients treated with combination immunotherapy as first-line treatment (Cohort 2). Each cohort was divided into long-term and short-term survival groups. All blood samples were collected before beginning immunotherapy. Serum metabolomic profiling was performed by UHPLC-Q-TOF MS analysis. Pareto-scaled principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis were performed. In Cohort 1, the mPFS and mOS of long-survival patients are 27.05 and NR months, respectively, and those of short-survival patients are 2.79 and 10.59 months. In Cohort 2, the mPFS and mOS of long-survival patients are 27.35 and NR months, respectively, and those of short-survival patients are 3.77 and 12.17 months. A total of 41 unique metabolites in Cohort 1 and 47 in Cohort 2 were screened. In Cohorts 1 and 2, there are 6 differential metabolites each that are significantly associated with both progression-free survival and overall survival. The AUC values for all groups ranged from 0.73 to 0.95. In cohort 1, the top 3 enriched KEGG pathways, as determined through significant different metabolic pathway analysis, were primary bile acid biosynthesis, African trypanosomiasis, and choline metabolism in cancer. In Cohort 2, the top 3 enriched KEGG pathways were the citrate cycle (TCA cycle), PPAR signaling pathway, and primary bile acid biosynthesis. The primary bile acid synthesis pathway had significant differences in the long-term and short-term survival groups in both Cohorts 1 and 2. Our study suggests that peripheral blood metabolomic analysis is critical for identifying metabolic biomarkers and pathways responsible for the patients with NSCLC treated with ICIs.
Insights
Metabolomic profiling of blood samples can predict long-term survival in non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs). This analysis identifies key metabolic pathways, like primary bile acid biosynthesis, associated with patient outcomes.
Area of Science:
- Oncology
- Immunotherapy
- Metabolomics
- Biomarker Discovery
Background:
- Immune checkpoint inhibitors (ICIs) show promise for non-small cell lung cancer (NSCLC), but predicting long-term survival remains challenging.
- Minimally invasive biomarkers are crucial for understanding treatment response and patient outcomes.
- Metabolomics offers a novel approach to identify predictive biomarkers in complex diseases like NSCLC.
Purpose of the Study:
- To evaluate the utility of serum metabolomic profiles in distinguishing long-term from short-term survival in NSCLC patients receiving ICIs.
- To identify specific metabolic biomarkers and pathways associated with progression-free survival (PFS) and overall survival (OS) in NSCLC patients treated with anti-PD-1 therapy.
Main Methods:
- Prospective recruitment of 97 stage IV NSCLC patients treated with anti-PD-1 inhibitors (mono- or combination immunotherapy).
- Serum metabolomic profiling using UHPLC-Q-TOF MS, followed by multivariate statistical analysis (PCA, OPLS-DA).
- Analysis of differential metabolites and enriched KEGG pathways in relation to survival outcomes.
Main Results:
- Significant differences in metabolic profiles were observed between long-term and short-term survival groups in both treatment cohorts.
- Six differential metabolites each were significantly associated with both PFS and OS in both cohorts, with AUC values ranging from 0.73 to 0.95.
- Primary bile acid biosynthesis pathway was significantly altered in both cohorts, distinguishing survival groups.
Conclusions:
- Peripheral blood metabolomic analysis can serve as a critical tool for identifying predictive biomarkers in NSCLC patients undergoing ICI therapy.
- Metabolic pathways, particularly primary bile acid biosynthesis, are strongly associated with survival outcomes in NSCLC patients treated with ICIs.
- These findings support the integration of metabolomics into clinical practice for personalized NSCLC treatment strategies.
