Mass spectrometry imaging of L-[ring-13C6]-labeled phenylalanine and tyrosine kinetics in non-small cell lung carcinoma

Abstract Background Metabolic reprogramming is a common phenomenon in tumorigenesis and tumor progression. Amino acids are important mediators in cancer metabolism, and their kinetics in tumor tissue are far from being understood completely. Mass spectrometry imaging is capable to spatiotemporally trace important endogenous metabolites in biological tissue specimens. In this research, we studied L-[ring-13C6]-labeled phenylalanine and tyrosine kinetics in a human non-small cell lung carcinoma (NSCLC) xenografted mouse model using matrix-assisted laser desorption/ionization Fourier-transform ion cyclotron resonance mass spectrometry imaging (MALDI-FTICR-MSI). Methods We investigated the L-[ring-13C6]-Phenylalanine (13C6-Phe) and L-[ring-13C6]-Tyrosine (13C6-Tyr) kinetics at 10 min (n = 4), 30 min (n = 3), and 60 min (n = 4) after tracer injection and sham-treated group (n = 3) at 10 min in mouse-xenograft lung tumor tissues by MALDI-FTICR-MSI. Results The dynamic changes in the spatial distributions of 19 out of 20 standard amino acids are observed in the tumor tissue. The highest abundance of 13C6-Phe was detected in tumor tissue at 10 min after tracer injection and decreased progressively over time. The overall enrichment of 13C6-Tyr showed a delayed temporal trend compared to 13C6-Phe in tumor caused by the Phe-to-Tyr conversion process. Specifically, 13C6-Phe and 13C6-Tyr showed higher abundances in viable tumor regions compared to non-viable regions. Conclusions We demonstrated the spatiotemporal intra-tumoral distribution of the essential aromatic amino acid 13C6-Phe and its de-novo synthesized metabolite 13C6-Tyr by MALDI-FTICR-MSI. Our results explore for the first time local phenylalanine metabolism in the context of cancer tissue morphology. This opens a new way to understand amino acid metabolism within the tumor and its microenvironment.

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Untargeted lipidomics of non-small cell lung carcinoma shows differentially abundant lipid classes in cancer vs non-cancer tissue

10.1101/2021.03.16.21253733 ◽

2021 ◽

Author(s):

Joshua M Mitchell ◽

Robert M Flight ◽

Andrew N Lane ◽

Hunter N.B. Moseley

Keyword(s):

Mass Spectrometry ◽

Lung Cancer ◽

Small Cell Lung Carcinoma ◽

Treatment Options ◽

Small Cell ◽

Metabolic Phenotype ◽

Small Cell Lung ◽

Cell Lung Carcinoma ◽

Genetic Subtypes ◽

Primary Nsclc

Lung cancer is the leading cause of cancer death worldwide and non-small cell lung carcinoma (NSCLC) represents 85% of newly diagnosed lung cancers. The high mortality rate of lung cancer is due in part to the lack of effective treatment options for advanced disease. A major limitation in the development of effective treatment options is our incomplete understanding of NSCLC metabolism at a molecular level, especially lipids. Improvements in mass spectrometry combined with our untargeted assignment tool SMIRFE enable the systematic and less biased examination of NSCLC lipid metabolism. Lipids were extracted from paired tumorous and non-tumorous lung tissue samples from 86 patients with suspected resectable stage I or IIa primary NSCLC and were analyzed using ultra-high resolution Fourier transform mass spectrometry. Pathological examination of the samples revealed that the majority of the samples were primary NSCLC; however, the disease group does include examples of metastases of other cancers and several granulomas. Information-content-informed (ICI) Kendall tau correlation analysis revealed correlation and co-occurrence patterns consistent with significant changes in lipid profiles between disease and non-disease samples. Lipids assigned using the program SMIRFE (Mitchell et al., 2019) were analyzed for differential abundance, followed by machine learning to classify the SMIRFE formula assignments into lipid categories. At the lipid category level, sterol abundances were consistently higher in diseased versus non-diseased lung tissues at statistically significant levels. The statistically significant increase in sterol abundances in primary NSCLC compared with non-cancerous lung tissue suggests for treatment of primary NSCLC a possible therapeutic role for statins and nitrogenous bisphosphonates, pharmaceuticals that inhibit endogenous sterol biosynthesis. This hypothesis is consistent with previous epidemiological studies that have identified a therapeutic role for statins in the treatment of NSCLC but were unable to identify a molecular mechanism for this effect. Additionally, the majority of the consistently increased sterol abundances belong to the sterol ester subcategory, suggesting increased SCD1 and ACAT1 activity. SCD1 expression is a known negative prognostic indicator for survival in NSCLC. In our study, a large fraction of the NSCLC samples displayed this phenotype; however, SCD1 mutants would be unexpected in all of these samples. This suggests that this metabolic phenotype may be shared across multiple genetic subtypes of NSCLC. Thus, inhibitors of SCD1 and other enzymes involved in the production of this metabolic phenotype could have utility in the treatment of many genetic subtypes of NSCLC.

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