4.6 Article

Metabolites as Prognostic Markers for Metastatic Non-Small Cell Lung Cancer (NSCLC) Patients Treated with First-Line Platinum-Doublet Chemotherapy

Journal

CANCERS
Volume 12, Issue 7, Pages -

Publisher

MDPI
DOI: 10.3390/cancers12071926

Keywords

non-small-cell-lung cancer; metabolomics; lipidomics; NMR; UPLC-MS; overall survival

Categories

Funding

  1. Alberta Cancer Foundation
  2. Alberta Innovates Health Solutions grants
  3. NIH [R21-CA-213234]
  4. Canadian Cancer Society [704970]

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The metabolic requirements of metastatic non-small cell lung (mNSCLC) tumors from patients receiving first-line platinum-doublet chemotherapy are hypothesized to imprint a blood signature suitable for survival prediction. Pre-treatment samples prospectively collected at baseline from a randomized phase III trial were assayed using nuclear magnetic resonance (NMR) spectroscopy (n= 341) and ultra-high performance liquid chromatography - mass spectrometry (UPLC-MS) (n= 297). Distributions of time to event outcomes were estimated by Kaplan-Meier analysis, and baseline characteristics adjusted Cox regression modeling was used to correlate markers' levels to time to event outcomes. Sixteen polar metabolites were significantly correlated with overall survival (OS) by univariate analysis (p< 0.025). Formate, 2-hydroxybutyrate, glycine andmyo-inositol were selected for a multivariate model. The median OS was 6.6 months in the high-risk group compared to 11.4 months in the low risk group HR (Hazard Ratio) = 1.99, 95% C.I. (Confidence Interval) 1.45-2.68;p< 0.0001). Modeling of lipids by class (sphingolipids, acylcarnitines and lysophosphatidylcholines) revealed a median OS = 5.7 months vs. 11. 9 months for the high vs. low risk group. (HR: 2.23, 95% C.I. 1.55-3.20;p< 0.0001). These results demonstrate that metabolic profiles from pre-treatment samples may be useful to stratify clinical outcomes for mNSCLC patients receiving chemotherapy. Genomic and longitudinal measurements pre- and post-treatment may yield addition information to personalize treatment decisions further.

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