Abstract:
Non-invasive diagnostics are crucial for the timely detection of renal cell carcinoma (RCC), significantly improving survival rates. Despite advancements, specific lipid markers for RCC remain unidentified. We aimed to discover and validate potent plasma markers and their association with dietary fats. Using lipid metabolite quantification, machine-learning algorithms, and marker validation, we identified RCC diagnostic markers in studies involving 60 RCC and 167 healthy controls (HC), as well as 27 RCC and 74 HC, by analyzing their correlation with dietary fats. RCC was associated with altered metabolism in amino acids, glycerophospholipids, and glutathione. We validated seven markers (l-tryptophan, various lysophosphatidylcholines [LysoPCs], decanoylcarnitine, and l-glutamic acid), achieving a 96.9% AUC, effectively distinguishing RCC from HC. Decreased decanoylcarnitine, due to reduced carnitine palmitoyltransferase 1 (CPT1) activity, was identified as affecting RCC risk. High intake of polyunsaturated fatty acids (PUFAs) was negatively correlated with LysoPC (18:1) and LysoPC (18:2), influencing RCC risk. We validated seven potential markers for RCC diagnosis, highlighting the influence of high PUFA intake on LysoPC levels and its impact on RCC occurrence via CPT1 downregulation. These insights support the efficient and accurate diagnosis of RCC, thereby facilitating risk mitigation and improving patient outcomes.
摘要:
非侵入性诊断对于及时发现肾细胞癌(RCC)至关重要。显著提高生存率。尽管取得了进步,RCC的特异性脂质标记仍未被识别。我们旨在发现和验证有效的血浆标志物及其与膳食脂肪的关联。使用脂质代谢物定量,机器学习算法,和标记验证,我们在涉及60例RCC和167例健康对照(HC)的研究中确定了RCC诊断标志物,以及27台RCC和74台HC,通过分析它们与膳食脂肪的相关性。RCC与氨基酸代谢改变有关,甘油磷脂,和谷胱甘肽.我们验证了七个标志物(l-色氨酸,各种溶血磷脂酰胆碱[LysoPCs],癸基肉碱,和l-谷氨酸),达到96.9%的AUC,有效区分碾压混凝土和HC。癸酸酰肉碱减少,由于肉碱棕榈酰转移酶1(CPT1)活性降低,被确定为影响RCC风险。高摄入多不饱和脂肪酸(PUFAs)与LysoPC(18:1)和LysoPC(18:2)呈负相关,影响碾压混凝土风险。我们验证了七个潜在的RCC诊断标志物,强调高PUFA摄入量对LysoPC水平的影响及其通过CPT1下调对RCC发生的影响。这些见解支持RCC的高效和准确诊断,从而促进风险缓解和改善患者预后。