留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

血清缬氨酸、甲硫氨酸浓度水平与乳腺癌临床特征及风险的相关性

解思琦 张恒瑀 李红万 谭明建 王青 李思嘉 郑凯 刘德权 唐诗聪

解思琦, 张恒瑀, 李红万, 谭明建, 王青, 李思嘉, 郑凯, 刘德权, 唐诗聪. 血清缬氨酸、甲硫氨酸浓度水平与乳腺癌临床特征及风险的相关性[J]. 昆明医科大学学报, 2022, 43(8): 47-55. doi: 10.12259/j.issn.2095-610X.S20220807
引用本文: 解思琦, 张恒瑀, 李红万, 谭明建, 王青, 李思嘉, 郑凯, 刘德权, 唐诗聪. 血清缬氨酸、甲硫氨酸浓度水平与乳腺癌临床特征及风险的相关性[J]. 昆明医科大学学报, 2022, 43(8): 47-55. doi: 10.12259/j.issn.2095-610X.S20220807
Siqi XIE, Hengyu ZHANG, Hongwan LI, Mingjian TAN, Qing WANG, Sijia LI, Kai ZHENG, Dequan LIU, Shicong TANG. Correlation between Serum Valine and Methionine Levels and Clinical Features and Risk of Breast Cancer[J]. Journal of Kunming Medical University, 2022, 43(8): 47-55. doi: 10.12259/j.issn.2095-610X.S20220807
Citation: Siqi XIE, Hengyu ZHANG, Hongwan LI, Mingjian TAN, Qing WANG, Sijia LI, Kai ZHENG, Dequan LIU, Shicong TANG. Correlation between Serum Valine and Methionine Levels and Clinical Features and Risk of Breast Cancer[J]. Journal of Kunming Medical University, 2022, 43(8): 47-55. doi: 10.12259/j.issn.2095-610X.S20220807

血清缬氨酸、甲硫氨酸浓度水平与乳腺癌临床特征及风险的相关性

doi: 10.12259/j.issn.2095-610X.S20220807
基金项目: 国家自然科学基金资助项目 (81960542,81960517);云南省教育厅科学研究基金资助项目 (2019J1288,2020J0198);云南省科技厅科技计划基础研究专项基金资助项目 (202001AU070053,202001AU070093);云南省高层次卫生计生技术人才培养基金资助项目 (H-2019075)
详细信息
    作者简介:

    解思琦 (1995~),女,云南曲靖人,在读医学硕士研究生,主要从事乳腺癌的临床诊疗工作

    通讯作者:

    刘德权,E-mail: liu_dequan2018@126. com

    唐诗聪,E-mail: tang_shicong@126.com

  • 中图分类号: R737.9

Correlation between Serum Valine and Methionine Levels and Clinical Features and Risk of Breast Cancer

  • 摘要:   目的   比较健康人群、乳腺良性肿瘤患者和乳腺癌患者的血清Val、Met浓度差异,探究血清缬氨酸和甲硫氨酸与乳腺癌临床特征及风险的关系。   方法   采用液相色谱-串联质谱法测定38名乳腺良性肿瘤患者,87名乳腺癌患者的血清Val、Met浓度,同时选择91名健康人群作为对照组。经Kruskal-Wallis H检验比较不同分组间的血清Val、Met浓度差异,分析不同化疗方案及手术方式对乳腺癌患者血清Val、Met浓度的影响。再通过二元Logistic回归分析、计算优势比和95%置信区间(CI)来评估血清Val、Met与乳腺癌的风险关系并绘制ROC曲线评估血清Val及Met对乳腺癌的诊断效能。   结果   与健康对照组相比,乳腺癌(BC)组的血清Val浓度水平高于乳腺良性肿瘤(BE)组和健康对照组,BC组和BE组的Met水平都高于健康对照组,差异有统计学意义(P < 0.05)。不同TNM分期及接受不同化疗方案的乳腺癌患者血清Val、Met浓度,差异无统计学意义( P > 0.05),但不同分子分型组间乳腺癌患者的血清Val浓度,差异有统计学意义( P < 0.05)。另外,血清Val浓度水平和乳腺癌风险无明显关系,但血清Met会显著影响乳腺癌的发生( P < 0.001),血清Met的浓度越高,乳腺癌的患病风险就越高,并且Met的浓度水平每增加一个单位,乳腺癌患病风险就增加24%( OR = 1.24 95% CI:1.15~1.34)。并且血清Met(P < 0.001)对乳腺癌的诊断具有统计学意义。其AUC为0.83、敏感度及特异性分别为69%和90.1%,临界值为19.76 μmol/L。   结论   乳腺癌患者的血清Val浓度高于乳腺良性肿瘤患者及健康人群;与健康人群相比,乳腺癌患者及乳腺良性肿瘤患者的血清Met浓度水平也有所升高。血清Val浓度水平和乳腺癌风险无明显关系,但血清Met与乳腺癌风险呈负相关,并且血清Met对乳腺癌诊断具有一定的诊断效能。
  • 图  1  血清Val、Met与乳腺癌的风险关系

    *P < 0.05。

    Figure  1.  The relationship between serum Val,Met and breast cancer risk

    图  2  乳腺癌组和健康对照组的血清Val、Met ROC曲线

    Figure  2.  Serum Val and Met ROC curves of breast cancer group and healthy control group

    表  1  不同分组的血清Val、Met浓度的比较(n = 216)

    Table  1.   Comparison of serum Val and Met concentrations in different groups (n=216)(M±IQR

    类别 健康对照组(n = 91) BE组(n = 38) BC组(n = 87) H P
    Val(μmlo/L) 161.32 ± 52.64 157.09 ± 42.35 185.63 ± 56.44 13.05 0.001*
    Met(μmlo/L) 14.03 ± 6.11 20.39 ± 6.45 24.28 ± 56.44 67.60 < 0.001 *
       *P < 0.05。
    下载: 导出CSV

    表  2  不同Val、Met浓度水平的乳腺癌患者基线特征

    Table  2.   Baseline characteristics of breast cancer patients with different concentrations of Val and Met

    分组 Val(μmlo/L) χ² P Met(μmlo/L) χ² P
    < 188.66( n=46) ≥188.66(n=41) < 27.74( n=53) ≥27.74(n=34)
    年龄(岁) 0.100 0.752 3.400 0.065
     < 50 22 21 22 21
     ≥50 24 20 31 13
    停经
     是 12 12 0.116 0.733 19 5 4.557 0.033*
     否 33 28 33 28
     未知 1 1 1 1
    初潮年龄(岁) 2.018 0.155 1.886 0.170
     < 14 15 18 16 17
     ≥14 26 16 27 15
     未知 5 7 10 2
    乳腺癌家族史 3.295 0.069 1.966 0.161
     有 6 1 6 1
     无 40 40 47 33
    BIM 3.172 0.205 0.526 0.769
     < 18.5 4 2 4 2
     ≤18.5 < 24 28 19 27 20
     ≥24 14 20 22 12
    TNM分期 5.616 0.060 0.059 0.971
     I-II 33 25 36 22
     III 7 13 12 8
     IV 3 0 2 1
     未知 3 3 3 3
    肿块大小(cm) 1.415 0.234 2.966 0.397
     Tx 5 6 8 3
     ≤2 21 15 25 11
     < 2≤5 15 19 17 17
     ≥5 1 1 1 1
     T4 4 0 2 2
    淋巴结转移 7.590 0.006* 0.011 0.915
     (+) 27 12 24 15
     (−) 19 29 29 19
    ER 2.769 0.096 0.041 0.839
     (+) 31 34 40 25
     (−) 15 7 13 9
    PR 2.305 0.129 0.079 0.778
     (+) 36 37 44 29
     (−) 10 4 9 5
    ki-67 0.123 0.726 0.311 0.577
     < 14% 13 13 17 9
     ≥14% 33 28 36 25
    HER-2b 0.774 0.379 1.576 0.209
     (+) 14 9 17 6
     (−) 28 28 33 23
    未知 4 4 3 5
    AR 0.289 0.591 0.429 0.513
     (+) 28 29 34 23
     (−) 8 6 7 7
     未知 10 6 12 4
    病理分型 0.006 0.002* 0.062 0.803
     浸润性导管癌 35 39 44 30
     浸润性小叶癌 1 2 2 1
     其他 10 0 7 3
    化疗史 0.346 0.557 8.746 0.003*
     有 31 30 31 30
     无 15 11 22 4
    经手术治疗 1.276 0.259 7.130 0.008*
     是 26 28 27 27
     否 20 13 26 7
    *P < 0.05。
    下载: 导出CSV

    表  3  不同分期乳腺癌患者的Val、Met浓度水平比较(n = 81)

    Table  3.   Comparison of levels of Val and Met in breast cancer patients in different stages (n = 81)

    类别 I期 II期 III期 IV期 F P
    n = 26(32%) n = 32(39%) n = 20(25%) n = 3(4%)
    Val(μmlo/L) 183.34 ± 54.03 186.37 ± 47.67 199.33 ± 45.91 158.01 ± 35.61 0.814 0.490
    Met(μmlo/L) 25.67 ± 10.90 29.73 ± 14.29 27.23 ± 18.06 23.95 ± 10.12 0.465 0.707
    下载: 导出CSV

    表  4  不同分子分型的乳腺癌患者Val、Met浓度水平比较(n = 80)

    Table  4.   Comparison of Val and Met concentrations in breast cancer patients with different molecular types (n = 80)

    类别 Luminal A型 Luminal B型 三阴型 HER-2阳性(HR阳性) HER-2阳性(HR阴性) F P
    n = 15(19%) n = 34(42%) n = 10(12.5%) n = 10(12.5%) n = 11(14%)
    Val(μmlo/L) 211.81 ± 81.40 191.81 ± 37.75 186.81 ± 58.75 193.05 ± 44.98 153.69 ± 30.13 3.403 0.023*
    Met(μmlo/L) 27.58 ± 13.03 29.35 ± 16.45 30.81 ± 21.23 26.53 ± 10.25 20.72 ± 7.36 0.822 0.515
       *P < 0.05。
    下载: 导出CSV

    表  5  不同化疗方案乳腺癌患者的Val、Met浓度水平比较(n = 61)

    Table  5.   Comparison of levels of Val and Met in breast cancer patients with different chemotherapy regimens (n = 61)

    类别 TC方案 AC方案 AC-T方案 其他方案 F P
    n = 11(18%) n = 22(36%) n = 22(36%) n = 6(10%)
    Val(μmlo/L) 187.45 ± 72.52 204.54 ± 54.89 193.71 ± 37.95 161.95 ± 51.19 1.084 0.363
    Met(μmlo/L) 26.12 ± 14.33 29.15 ± 10.57 35.76 ± 18.43 23.18 ± 11.59 1.836 0.151
      TC:紫衫醇 + 环磷酰胺;AC:蒽环类药物+环磷酰胺;AC-T:蒽环类药物+环磷酰胺序贯紫杉醇;其他:除以上化疗方案的其他方案。
    下载: 导出CSV

    表  6  乳腺癌组和健康对照组血清Met的ROC曲线下面积(AUC)、敏感度(%)和特异性(%)及 95% CI参数

    Table  6.   Area under the ROC curve (AUC),sensitivity (%),specificity (%) and 95% CI parameters of serum Met in breast cancer group and healthy control group

    氨基酸 P AUC 临界值
    (μmlo/L)
    敏感度(%) 特异性(%) 95% CI
    Met < 0.001 * 0.83 19.76 69 90.1 0.76~0.89
       *P < 0.05。
    下载: 导出CSV
  • [1] Sung H,Ferlay J,Siegel R L,et al. Global cancer statistics 2020:GLOBOCAN Estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J]. CA:A Cancer Journal for Clinicians,2021,71(3):209-249. doi: 10.3322/caac.21660
    [2] Wang X,Zhao X,Chou J,et al. Taurine,glutamic acid and ethylmalonic acid as important metabolites for detecting human breast cancer based on the targeted metabolomics[J]. Cancer Biomarkers:Section A of Disease Markers,2018,23(2):255-268.
    [3] Miyagi Y,Higashiyama M,Gochi A,et al. Plasma free amino acid profiling of five types of cancer patients and its application for early detection[J]. PloS One,2011,6(9):24143. doi: 10.1371/journal.pone.0024143
    [4] Cha Y J,Kim E S,Koo J S. Amino acid transporters and glutamine metabolism in breast cancer[J]. International Journal of Molecular Sciences,2018,19(3):907. doi: 10.3390/ijms19030907
    [5] Guo Chong C,Choul C J,Jiaqian X,et al. Healthful eating patterns,serum metabolite profile and risk of diabetes in a population-based prospective study of US Hispanics/Latinos[J]. Diabetologia,2022,65(7):1133-1144. doi: 10.1007/s00125-022-05690-w
    [6] Leichtle A B,Nuoffer J M,Ceglarek U,et al. Serum amino acid profiles and their alterations in colorectal cancer[J]. Metabolomics:Official Journal of the Metabolomic Society,2012,8(4):643-653.
    [7] Nasimi H,Madsen J S,Zedan A H,et al. Correlation between stage of prostate cancer and tyrosine and tryptophan in urine samples measured electrochemically[J]. Analytical Biochemistry,2022,64(9):114698.
    [8] Sivanand S,Vander Heiden M G. Emerging roles for branched-Chain amino acid metabolism in cancer[J]. Cancer Cell,2020,37(2):147-156. doi: 10.1016/j.ccell.2019.12.011
    [9] Li Z,Zhang H. Reprogramming of glucose,fatty acid and amino acid metabolism for cancer progression[J]. Cellular and Molecular Life Sciences:CMLS,2016,73(2):377-392. doi: 10.1007/s00018-015-2070-4
    [10] Van Geldermalsen M,Quek L E,Turner N,et al. Benzylserine inhibits breast cancer cell growth by disrupting intracellular amino acid homeostasis and triggering amino acid response pathways[J]. BMC Cancer,2018,18(1):689. doi: 10.1186/s12885-018-4599-8
    [11] Kou F,Zhu B,Zhou W,et al. Targeted metabolomics in the cell culture media reveals increased uptake of branched amino acids by breast cancer cells[J]. Analytical Biochemistry,2021,62(4):114192.
    [12] Eniu D T,Romanciuc F,Moraru C,et al. The decrease of some serum free amino acids can predict breast cancer diagnosis and progression[J]. Scandinavian Journal of Clinical and Laboratory Investigation,2019,79(1-2):17-24. doi: 10.1080/00365513.2018.1542541
    [13] Poschke I,Mao Y,Kiessling R,et al. Tumor-dependent increase of serum amino acid levels in breast cancer patients has diagnostic potential and correlates with molecular tumor subtypes[J]. Journal of Translational Medicine,2013,16(11):290.
    [14] Pranjali J,Neha S,Gaurav R,et al. Performance evaluation of digital mammography,digital breast tomosynthesis and ultrasound in the detection of breast cancer using pathology as gold standard:An institutional experience[J]. Egyptian Journal of Radiology and Nuclear Medicine,2022,53(1):48-52. doi: 10.1186/s43055-022-00714-2
    [15] Barnes T,Bell K,DiSebastiano K M,et al. Plasma amino acid profiles of breast cancer patients early in the trajectory of the disease differ from healthy comparison groups[J]. Applied Physiology,Nutrition,and Metabolism = Physiologie Appliquée,Nutrition et Métabolisme,2014,39(6):740-744. doi: 10.1139/apnm-2013-0526
    [16] Stine Z E,Schug Z T,Salvino J M,et al. Targeting cancer metabolism in the era of precision oncology[J]. Nature Reviews. Drug Discovery,2022,21(2):141-162. doi: 10.1038/s41573-021-00339-6
    [17] Thandapani P,Kloetgen A,Witkowski M T,et al. Valine tRNA levels and availability regulate complex I assembly in leukaemia[J]. Nature,2022,601(7893):428-433. doi: 10.1038/s41586-021-04244-1
    [18] Butler M,van der Meer L T,van Leeuwen F N. Amino acid depletion therapies:Starving cancer cells to death[J]. Trends in Endocrinology and Metabolism:TEM,2021,32(6):367-381. doi: 10.1016/j.tem.2021.03.003
    [19] Jeon H,Kim J H,Lee E,et al. Methionine deprivation suppresses triple-negative breast cancer metastasis in vitro and in vivo[J]. Oncotarget,2016,7(41):67223-67234. doi: 10.18632/oncotarget.11615
    [20] Cheng F,Wang Z,Huang Y,et al. Investigation of salivary free amino acid profile for early diagnosis of breast cancer with ultra performance liquid chromatography-mass spectrometry[J]. Clinica Chimica Acta; International Journal of Clinical Chemistry,2015,44(7):23-31.
    [21] Mizota Y,Yamamoto S. Prevalence of breast cancer risk factors in Japan[J]. Japanese Journal of Clinical Oncology,2012,42(11):1008-1012. doi: 10.1093/jjco/hys144
    [22] Ma N,Ma X. Dietary amino acids and the gut-microbiome-immune axis:Physiological metabolism and therapeutic prospects[J]. Comprehensive Reviews in Food Science and Food Safety,2019,18(1):221-242. doi: 10.1111/1541-4337.12401
    [23] Hou Y,Hu S,Li X,et al. Amino acid metabolism in the liver:Nutritional and physiological significance[J]. Advances in Experimental Medicine and Biology,2020,126(5):21-37.
    [24] Nagata C,Wada K,Tsuji M,et al. Plasma amino acid profiles are associated with biomarkers of breast cancer risk in premenopausal Japanese women[J]. Cancer Causes & Control:CCC,2014,25(2):143-149.
    [25] Tobias D K,Chai B,Tamimi R M,et al. Dietary intake of branched Chain amino acids and breast cancer Risk in the NHS and NHS II prospective cohorts[J]. JNCI Cancer Spectrum,2021,5(3):32.
  • [1] 张正, 杨艳红, 冯再辉, 詹路江, 普金仙, 段茜婷.  高场强MRIT1灌注成像联合DWI成像在评估乳腺癌新辅助化疗疗效中的价值, 昆明医科大学学报. doi: 10.12259/j.issn.2095-610X.S20240722
    [2] 宋文娟, 马雪娟, 孙钺, 谷颖, 叶雨佳, 李姝墨, 葛菲, 刘利萍, 赵月, 王钰.  超声心动图三维斑点追踪技术对乳腺癌曲妥珠单抗治疗中心脏毒性评估的应用, 昆明医科大学学报. doi: 10.12259/j.issn.2095-610X.S20230217
    [3] 严梅, 关琼瑶, 王垣晓, 顾丽琪, 柘磊, 刘莉娟, 郝润珍, 苏艳, 黄思思.  乳腺癌根治性手术后患者及配偶未满足需求与二元应对水平的关系, 昆明医科大学学报. doi: 10.12259/j.issn.2095-610X.S20230410
    [4] 胡滔, 吴怡, 耿文达, 章意坚, 贺瑄, 李珊珊, 习杨彦彬, 邓丽玲.  自主运动训练通过调节Caspase-3的活性抑制人BRCA1突变乳腺癌的增殖与生长, 昆明医科大学学报. doi: 10.12259/j.issn.2095-610X.S20230419
    [5] 刘婧, 严梅, 陈亚爽, 杜丽钰, 黄思思.  基于Kano模型的乳腺癌根治性手术后患者支持性照护需求调查, 昆明医科大学学报. doi: 10.12259/j.issn.2095-610X.S20231129
    [6] 廖佳伟, 胡晓庆, 杨毅.  乳腺癌根治术患者放化疗前后甲状腺功能变化情况及其临床意义, 昆明医科大学学报. doi: 10.12259/j.issn.2095-610X.S20220229
    [7] 孙文婧, 胡曼婷, 李娜, 葛菲, 陈文林, 刘洋.  乳腺癌内分泌治疗耐药及其逆转的研究进展, 昆明医科大学学报. doi: 10.12259/j.issn.2095-610X.S20210724
    [8] 张江, 刘燕, 李文辉, 赵喜娟, 陈正庭, 关琼瑶, 吴江.  睡前音乐疗法对乳腺癌放疗患者睡眠质量和癌因性疲乏的影响, 昆明医科大学学报. doi: 10.12259/j.issn.2095-610X.S20201248
    [9] 段佳君, 刘德权, 张勇.  影响女性育龄期乳腺癌患者对生育能力受损风险认识及保留生育能力决策的因素, 昆明医科大学学报.
    [10] 李晨, 杨明莹, 段文晶, 蒋爱梅, 黄琪, 杨学芳.  女性乳腺癌患者首次化疗前心理痛苦现状及相关因素, 昆明医科大学学报.
    [11] 张琰晔, 李荣清, 张勇.  乳腺癌在螺旋断层放射治疗中的研究进展, 昆明医科大学学报.
    [12] 李宁, 徐妙, 张维, 张倩, 孔鹰.  乳腺癌患者放化疗前后维生素D水平的变化, 昆明医科大学学报.
    [13] 赵云红, 傅大干, 唐一吟, 郝芳, 史峭铭, 张丽娟.  昆明市2015年至2016年城市乳腺癌高风险人群筛查结果分析, 昆明医科大学学报.
    [14] 王怡茗, 杨越.  乳腺钼靶和超声检查对于诊断乳腺癌的价值对比, 昆明医科大学学报.
    [15] 郭学君, 缪春梅, 汤清雯, 金学梅, 杨越.  乳腺癌患者甲状腺超声影像的占位性改变, 昆明医科大学学报.
    [16] 李云芬.  CCDC8基因表达与乳腺癌分子分型的相关性研究, 昆明医科大学学报.
    [17] 李晓勇.  Th17/Treg平衡失调及其相关因子在乳腺癌浸润转移的相关性研究, 昆明医科大学学报.
    [18] 赵春芳.  干扰RNA抑制EGFR对乳腺癌细胞放射敏感性的影响, 昆明医科大学学报.
    [19] 李昆仑.  RNAi抑制Survivin基因的表达对乳腺癌SKBr-3细胞的影响, 昆明医科大学学报.
    [20] 乙型肝炎患者氨基酸代谢与同型半胱氨酸浓度变化分析, 昆明医科大学学报.
  • 加载中
图(2) / 表(6)
计量
  • 文章访问数:  3438
  • HTML全文浏览量:  2481
  • PDF下载量:  32
  • 被引次数: 0
出版历程
  • 收稿日期:  2022-03-05
  • 刊出日期:  2022-08-25

目录

    /

    返回文章
    返回