Mitchell Joshua M, Flight Robert M, Moseley Hunter N B
Department of Molecular & Cellular Biochemistry, University of Kentucky, Lexington, KY 40536, USA.
Markey Cancer Center, University of Kentucky, Lexington, KY 40536, USA.
Metabolites. 2021 Oct 28;11(11):740. doi: 10.3390/metabo11110740.
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.
肺癌仍然是全球癌症死亡的主要原因,非小细胞肺癌(NSCLC)占新诊断肺癌的85%。在本研究中,我们利用非靶向分析工具小分子同位素分辨分子式枚举器(SMIRFE)和超高分辨率傅里叶变换质谱,检测了86例疑似I期或IIA期原发性NSCLC患者配对的癌性和非癌性肺组织样本之间的脂质谱差异。相关性和共现分析揭示了癌组织和非癌组织样本之间存在显著的脂质谱差异。对差异丰富的分子式的机器学习脂质类别进行进一步分析,发现在NSCLC样本中存在高丰度固醇、高丰度和高m/z鞘脂以及低丰度甘油磷脂代谢表型。在类别水平上,观察到固醇酯丰度较高,心磷脂丰度较低,这分别表明硬脂酰辅酶A去饱和酶1(SCD1)或乙酰辅酶A乙酰转移酶(ACAT1)活性改变,以及人的心磷脂合酶1或溶血心磷脂酰基转移酶活性改变,后者已知具有抗凋亡作用。在多种基因不同的NSCLC亚型中存在共同的代谢表型,这表明该表型是NSCLC发展所必需的,可能由多种不同的基因损伤导致。因此,针对共同受影响的途径可能对多种基因不同的NSCLC亚型有益。