American Association for Cancer Research
Browse

Supplementary Materials and Methods, Figures 1 - 10, Tables 1 - 4 from Noninvasive Urinary Metabolomic Profiling Identifies Diagnostic and Prognostic Markers in Lung Cancer

Download (1.36 MB)
journal contribution
posted on 2023-03-30, 22:40 authored by Ewy A. Mathé, Andrew D. Patterson, Majda Haznadar, Soumen K. Manna, Kristopher W. Krausz, Elise D. Bowman, Peter G. Shields, Jeffrey R. Idle, Philip B. Smith, Katsuhiro Anami, Dickran G. Kazandjian, Emmanuel Hatzakis, Frank J. Gonzalez, Curtis C. Harris

PDF file - 1526KB, Supplementary Table 1 shows random forest analysis results for predictions of lung cancer status in the training set. Supplementary Table 2 shows associations with survival in the training set when the top four predictive metabolites are combined in all cases. Supplementary Table 3 shows associations with survival in the training set, stratified by self-reported race. Supplementary Table 4 shows intraclass correlation coefficients in the quantitated subset. Supplementary Figure 1 depicts workflow of the classification analysis. Supplementary Figure 2 depicts quality control assessment in the training set. Supplementary Figure 3 shows predictions of smoking status in the training set determined by random forest analysis and abundances of tobacco-related metabolites. Supplementary Figure 4 shows overlap of metabolites predictive of lung cancer status in the training set based on random forest analysis, stratified by gender, race and smoking status. Supplementary Figure 5 shows fragmentation patterns of top four predictive metabolites determined by tandem mass spectrometry. Supplementary Figure 6 depicts identification of creatine riboside by NMR. Supplementary Figure 7 shows diurnal effects on top four predictive metabolites. Supplementary Figure 8 shows top four predictive metabolite abundances stratified by smoking status. Supplementary Figure 9 shows Kaplan-Meier survival estimates in the training set depicted for the top four predictive metabolites in stages I-II and their combination. Supplementary Figure 10 shows metabolite abundances stratified by chemotherapy/radiation status and surgery status.

History

ARTICLE ABSTRACT

Lung cancer remains the most common cause of cancer deaths worldwide, yet there is currently a lack of diagnostic noninvasive biomarkers that could guide treatment decisions. Small molecules (<1,500 Da) were measured in urine collected from 469 patients with lung cancer and 536 population controls using unbiased liquid chromatography/mass spectrometry. Clinical putative diagnostic and prognostic biomarkers were validated by quantitation and normalized to creatinine levels at two different time points and further confirmed in an independent sample set, which comprises 80 cases and 78 population controls, with similar demographic and clinical characteristics when compared with the training set. Creatine riboside (IUPAC name: 2-{2-[(2R,3R,4S,5R)-3,4-dihydroxy-5-(hydroxymethyl)-oxolan-2-yl]-1-methylcarbamimidamido}acetic acid), a novel molecule identified in this study, and N-acetylneuraminic acid (NANA) were each significantly (P < 0.00001) elevated in non–small cell lung cancer and associated with worse prognosis [HR = 1.81 (P = 0.0002), and 1.54 (P = 0.025), respectively]. Creatine riboside was the strongest classifier of lung cancer status in all and stage I-II cases, important for early detection, and also associated with worse prognosis in stage I-II lung cancer (HR = 1.71, P = 0.048). All measurements were highly reproducible with intraclass correlation coefficients ranging from 0.82 to 0.99. Both metabolites were significantly (P < 0.03) enriched in tumor tissue compared with adjacent nontumor tissue (N = 48), thus revealing their direct association with tumor metabolism. Creatine riboside and NANA may be robust urinary clinical metabolomic markers that are elevated in tumor tissue and associated with early lung cancer diagnosis and worse prognosis. Cancer Res; 74(12); 3259–70. ©2014 AACR.

Usage metrics

    Cancer Research

    Licence

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC