Abstract
Lung cancer remains the leading cause of cancer death worldwide and non-small cell lung carcinoma (NSCLC) represents 85% of newly diagnosed lung cancers. In this study, we utilized our untargeted assignment tool Small Molecule Isotope Resolved Formula Enumerator (SMIRFE) and ultra-high-resolution Fourier transform mass spectrometry to examine lipid profile differences between paired cancerous and non-cancerous lung tissue samples from 86 patients with suspected stage I or IIA primary NSCLC. Correlation and co-occurrence analysis revealed significant lipid profile differences between cancer and non-cancer samples. Further analysis of machine-learned lipid categories for the differentially abundant molecular formulas identified a high abundance sterol, high abundance and high m/z sphingolipid, and low abundance glycerophospholipid metabolic phenotype across the NSCLC samples. At the class level, higher abundances of sterol esters and lower abundances of cardiolipins were observed suggesting altered stearoyl-CoA desaturase 1 (SCD1) or acetyl-CoA acetyltransferase (ACAT1) activity and altered human cardiolipin synthase 1 or lysocardiolipin acyltransferase activity respectively, the latter of which is known to confer apoptotic resistance. The presence of a shared metabolic phenotype across a variety of genetically distinct NSCLC subtypes suggests that this phenotype is necessary for NSCLC development and may result from multiple distinct genetic lesions. Thus, targeting the shared affected pathways may be beneficial for a variety of genetically distinct NSCLC subtypes.
| Original language | English |
|---|---|
| Article number | 740 |
| Journal | Metabolites |
| Volume | 11 |
| Issue number | 11 |
| DOIs | |
| State | Published - Nov 2021 |
Bibliographical note
Publisher Copyright:© 2021 by the authors. Licensee MDPI, Basel, Switzerland.
Funding
Funding: The work was supported in part by grants NSF 1419282 (PI Moseley), NSF 2020026 (PI Moseley), NIH 1P01CA163223-01A1 (PD Lane), 1U24DK097215-01A1 (PD Higashi), and P30 CA177558 (B.M. Evers, PI) via the Markey Cancer Center Biostatistics and Bioinformatics Shared Resource Facility (MCC BB-SRF). The work was supported in part by grants NSF 1419282 (PI Moseley), NSF 2020026 (PI Moseley), NIH 1P01CA163223-01A1 (PD Lane), 1U24DK097215-01A1 (PD Higashi), and P30 CA177558 (B.M. Evers, PI) via the Markey Cancer Center Biostatistics and Bioinformatics Shared Resource Facility (MCC BB-SRF). We thank Timothy Fahrenholz for his efforts in mass spectrometry data collection. We thank Andrew Lane, Teresa Fan, and Rick Higashi for their efforts in human tissue sample collection and sample preparation. We also thank Andrew Lane for his contributions and revisions to an early version of the manuscript.
| Funders | Funder number |
|---|---|
| Markey Cancer Center Biostatistics and Bioinformatics Shared Resource Facility | |
| Masonic Cancer Center, University of Minnesota | |
| National Science Foundation Arctic Social Science Program | 1419282, 2020026 |
| National Institutes of Health (NIH) | P30 CA177558, 1U24DK097215-01A1, 1P01CA163223-01A1 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Fourier-transform mass spectrometry
- Lipidomics
- Non-small cell lung carcinoma
- SMIRFE
ASJC Scopus subject areas
- Endocrinology, Diabetes and Metabolism
- Biochemistry
- Molecular Biology
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