基于非靶标代谢组学的肺腺癌软脑膜转移患者脑脊液代谢特征研究

摘要/Abstract

摘要：

目的分析脑脊液中代谢标志物在晚期肺腺癌软脑膜转移（LM）中的诊断价值。方法收集2019年12月至2021年12月于南京大学医学院附属鼓楼医院就诊的肺腺癌LM患者脑脊液样本46例（LM组）,另外选取同期神经系统良性疾病患者的脑脊液样本48例（对照组）,采用高效液相色谱-质谱技术对脑脊液进行代谢组学分析,应用主成分分析（PCA）和正交偏最小二乘判别分析法（OPLS-DA）进行建模,采用多标准评价体系寻找两组间差异性代谢产物,并利用受试者工作特征（ROC）曲线、通路富集分析等方法,筛选与肺腺癌LM发病相关的代谢物及其通路。结果LM组与对照组间的年龄（Z=-0.41,P=0.210）、性别（χ²=1.19,P=0.275）、吸烟史（χ²=2.86,P=0.091）、Karnofsky功能状态评分（χ²=0.65,P=0.419）及颅内压增高比例（χ²=0.65,P=0.419）差异均无统计学意义。PCA模型（正离子与负离子模式下,R2X分别为0.608和0.583,Q2分别为0.462和0.513）和OPLS-DA模型（正离子与负离子模式下,R2Y分别为0.967和0.889,Q2分别为0.959和0.852）显示整体数据质量良好,具有较好的解释率和预测率,对数据进行200次重采集验证,不存在过度拟合现象。两组人群代谢轮廓有显著差别,应用多标准评价体系共筛选出30个内源性差异性代谢物,通过ROC曲线分析确定了曲线下面积（AUC）较大的6种潜在的生物标志物,包括酪氨酸（AUC=0.967,95%CI为0.906~1.000）、苯丙氨酸（AUC=0.992,95%CI为0.973~1.000）、丙酮酸（AUC=0.976,95%CI为0.935~1.000）、色氨酸（AUC=0.935,95%CI为0.880~0.973）、葡萄糖（AUC=0.932,95%CI为0.880~0.975）、一磷酸腺苷（AUC=0.993,95%CI为0.987~1.000）。将筛选的30种差异性代谢产物进行代谢通路富集分析,匹配到20条相关的代谢通路,其中最可能引起代谢产物变化的4条代谢通路为：糖酵解及糖代谢合成,丙酮酸代谢,苯丙氨酸代谢,苯丙氨酸、酪氨酸和色氨酸生物合成。结论非靶向代谢组学可有效筛查肺腺癌LM患者特异的脑脊液代谢物,6种潜在的代谢物如酪氨酸、苯丙氨酸、丙酮酸、色氨酸、一磷酸腺苷、葡萄糖及其代谢通路可能参与肺腺癌LM的发病过程。

关键词:代谢组学,肺腺癌,软脑膜转移,脑脊液

Abstract:

ObjectiveTo analyze the diagnostic value of metabolic makers in cerebrospinal fluid in advanced lung adenocarcinoma patients with leptomeningeal metastases （LM）.MethodsA total of 46 cerebrospinal fluid samples （LM group） from lung adenocarcinoma patients with LM admitted to Nanjing Drum Tower Hospital Affiliated to Nanjing University Medical School from December 2019 to December 2021 were collected, and 48 cerebrospinal fluid samples （control group） from patients with benign neurological diseases during the same period were collected. Metabolomics analysis of cerebrospinal fluid was carried out by high-performance liquid chromatography-mass spectrometry. Principle component analysis （PCA） and orthogonal to partial least squares discriminant analysis （OPLS-DA） were used for modeling. Multi-criteria assessment was used to identify the different metabolites between the two groups. Receiver operating characteristic （ROC） curve, pathway enrichment analysis and other methods were used to screen metabolites and pathways related to LM from lung adenocarcinoma.ResultsThere were no statistically significant differences in the proportions of age （Z=-0.41,P=0.210）, gender （χ²=1.19,P=0.275）, history of smoking （χ²=2.86,P=0.091）, Karnofsky performance status score （χ²=0.65,P=0.419） and increased intracranial pressure （χ²=0.65,P=0.419） between the LM group and control group. The models of PCA （R2X was 0.608 and 0.583, Q2 was 0.462 and 0.513 in electrospray ion positive and negative modes, respectively） and OPLS-DA （R2Y was 0.967 and 0.889, Q2 was 0.959 and 0.852 in electrospray ion positive and negative modes, respectively） showed that the overall data quality was good. Meanwhile, the model interpretation rate and prediction rate were effective. The permutation tests duplicated for 200 times and showed no over-fitting of the established model. The metabolic profiles of the two groups were significantly different. A total of 30 endogenously differential metabolites were screened by using multi-criteria assessment. Six potential biomarkers with larger area under the curve （AUC） were identified through ROC curve analysis, including tyrosine （AUC=0.967, 95%CI： 0.906-1.000）, phenylalanine （AUC=0.992, 95%CI： 0.973-1.000）, pyruvate （AUC=0.976, 95%CI： 0.935-1.000）, tryptophan （AUC=0.935, 95%CI： 0.880-0.973）, glucose （AUC=0.932, 95%CI： 0.880-0.975） and adenosine monophosphate （AUC=0.993, 95%CI： 0.987-1.000）. The 30 selected differential metabolites were enriched and analyzed for metabolic pathways, and 20 relevant metabolic pathways were matched. Among them, the four metabolic pathways most likely to cause changes in metabolites were glycolysis and glucose metabolic synthesis, pyruvate metabolism, phenylalanine metabolism, phenylalanine, tyrosine and tryptophan biosynthesis.ConclusionUntargeted metabolomics analysis can effectively screen specific cerebrospinal fluid metabolites in lung adenocarcinoma patients with LM. Six potential metabolites such as tyrosine, phenylalanine, pyruvate, tryptophan, adenosine monophosphate, glucose and their metabolic pathways may be involved in the pathogenesis of LM from lung adenocarcinoma.

Key words:Metabolomics,Lung adenocarcinoma,Leptomeningeal metastases,Cerebrospinal fluid

林永娟, 李会颖, 尹震宇, 郭爱斌, 谢宇. 基于非靶标代谢组学的肺腺癌软脑膜转移患者脑脊液代谢特征研究[J]. 国际肿瘤学杂志, 2022, 49(7): 390-399.

Lin Yongjuan, Li Huiying, Yin Zhenyu, Guo Aibin, Xie Yu. Investigation of cerebrospinal fluid metabolites in patients with leptomeningeal metastases from lung adenocarcinoma based on untargeted metabolomics[J]. Journal of International Oncology, 2022, 49(7): 390-399.

图/表9

表1

两组患者临床资料比较[例（%）/M（Q1,Q3）]"

基本指标	LM组（n=46）	对照组（n=48）	χ²/Z值	P值
性别
男	30（65.22）	26（54.17）	1.19	0.275
女	16（34.78）	22（45.83）	1.19	0.275
年龄（岁）	57.00（52.00,63.00）	57.50（52.00,64.00）	-0.41	0.210
吸烟史
是	16（34.78）	25（52.08）	2.86	0.091
否	30（65.22）	23（47.92）	2.86	0.091
KPS评分（分）
<70	16（34.78）	13（27.08）	0.65	0.419
≥70	30（65.22）	35（72.92）	0.65	0.419
颅内压（kPa）
>1.77	30（65.22）	35（72.92）	0.65	0.419
≤1.77	16（34.78）	13（27.08）	0.65	0.419

表1

图1

图2

表2

46例肺腺癌软脑膜转移患者与48例神经系统良性疾病患者脑脊液中差异性代谢物比较"

代谢物	保留时间（min）	质荷比	变化倍数	VIP	P值	代谢物	保留时间（min）	质荷比	变化倍数	VIP	P值
胆碱	0.24	104.11	15.28	1.16	0.024	5-羟基-L色氨酸	10.22	220.22	20.34	1.16	0.003
酪氨酸	0.62	182.08	691.81	1.28	0.001	花生四烯酸	10.26	303.24	2.62	1.10	0.025
吡哆醇	0.63	184.06	11.54	1.47	0.029	γ-亚麻酸	12.77	280.45	98.45	1.21	0.012
苯丙氨酸	0.65	164.07	896.92	1.20	<0.001	泛酸	0.55	219.24	4.15	1.02	0.012
酮亮氨酸	1.50	129.06	2.61	1.35	0.006	色氨酸	0.64	205.10	589.27	1.48	0.014
3-磷酸甘油	1.52	172.07	44.22	1.13	0.016	甘油醛	0.64	89.02	32.67	1.71	0.017
L-组氨酸	2.19	254.11	6.66	1.27	0.005	鸟嘌呤	1.23	145.67	101.36	1.11	0.003
前列腺素B2	3.36	334.45	26.44	1.29	0.025	腺苷A	2.05	246.30	25.17	1.71	0.005
乳酸	5.65	85.20	21.62	1.22	0.002	三磷酸鸟苷	2.35	523.18	646.31	1.00	0.006
丙酮酸	5.79	79.89	694.81	1.29	<0.001	一磷酸腺苷	7.06	347.22	44.11	1.72	<0.001
2-羟基丁酸	5.80	113.67	164.31	1.35	0.004	赖氨酸	12.88	135.53	79.35	1.73	0.004
丙氨酸	6.59	74.12	140.33	1.31	0.015	谷氨酰胺	14.32	164.23	69.53	1.77	0.001
白三烯B4	7.06	335.22	70.72	1.05	0.011	葡萄糖	17.12	124.50	512.52	1.06	<0.001
α-亚麻酸	7.07	277.22	78.94	1.17	0.019	乙酸	18.56	65.67	37.32	1.09	0.001
甘油磷酸胆碱	8.04	237.12	24.95	1.15	0.042	核糖醇	19.56	125.67	2.95	1.66	0.005

表2

图3

图4

代谢物	AUC	敏感性（%）	特异性（%）	95%CI
酪氨酸	0.967	93.50	100.00	0.906~1.000
苯丙氨酸	0.992	97.80	100.00	0.973~1.000
丙酮酸	0.976	95.70	97.90	0.935~1.000
色氨酸	0.935	87.00	85.40	0.880~0.973
葡萄糖	0.932	93.50	81.20	0.880~0.975
一磷酸腺苷	0.993	97.80	93.80	0.987~1.000

表3

表4

预测肺腺癌LM显著性较高的20条代谢通路信息表"

序号	信号通路	P值
1	氨基酰基-tRNA生物合成	1.63×10^-5
2	糖酵解及糖代谢合成	1.11×10^-3
3	苯丙氨酸、酪氨酸和色氨酸生物合成	1.98×10^-3
4	丙酮酸代谢	7.14×10^-3
5	苯丙氨酸代谢	1.39×10^-2
6	丙氨酸、天冬氨酸和谷氨酸代谢	1.41×10^-2
7	乙醛酸盐和二羧酸酯代谢	2.03×10^-2
8	不饱和脂肪酸的生物合成	2.78×10^-2
9	脂代谢	2.77×10^-2
10	嘌呤代谢	3.04×10^-2
11	谷氨酰胺代谢	0.011
12	氮代谢	0.021
13	甘氨酸、丝氨酸和苏氨酸代谢	0.022
14	缬氨酸、亮氨酸和异亮氨酸生物合成	0.025
15	花生四烯酸酸代谢	0.030
16	泛醌和其他萜类化合物-醌生物合成	0.036
17	维生素B6代谢	0.037
18	生物素代谢	0.040
19	色氨酸代谢	0.041
20	酪氨酸代谢	0.048

表4

图5

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