GC-MS based metabolite fingerprinting of serous ovarian carcinoma and benign ovarian tumor

被引:7
|
作者
Eroglu, Evren Caglar [1 ]
Gulec, Umran Kucukgoz [2 ]
Vardar, Mehmet Ali [2 ]
Paydas, Semra [3 ]
机构
[1] Alata Hort Res Inst, Mersin, Turkey
[2] Cukurova Univ, Med Fac, Dept Gynecol Oncol, Adana, Turkey
[3] Cukurova Univ, Med Fac, Dept Oncol, Adana, Turkey
关键词
metabolomics; biomarker; ovarian cancer; benign tumor; healthy control; GC-MS; OPLS-DA; BIOMARKER DISCOVERY; MASS-SPECTROMETRY; PROSTATE-CANCER; METABOLOMICS; DIAGNOSIS; URINE; SERUM; IDENTIFICATION; PLASMA;
D O I
10.1177/14690667221098520
中图分类号
O64 [物理化学(理论化学)、化学物理学]; O56 [分子物理学、原子物理学];
学科分类号
070203 ; 070304 ; 081704 ; 1406 ;
摘要
The aim of this study is to identify urinary metabolomic profile of benign and malign ovarian tumors patients. Samples were analyzed using gas chromatography-mass spectrometry (GC-MS) and metabolomic tools to define biomarkers that cause differentiation between groups. 7 metabolites were found to be different in patients with ovarian cancer (OC) and benign tumors (BT). R2Y and Q2 values were found to be 0.670 and 0.459, respectively. L-tyrosine, glycine, stearic acid, turanose and L-threonine metabolites were defined as prominent biomarkers. The sensitivity of the model was calculated as 90.72% and the specificity as 82.09%. In the pathway analysis, glutathione metabolism, aminoacyl-tRNA biosynthesis, glycine serine and threonine metabolic pathway, primary bile acid biosynthesis pathways were found to be important. According to the t-test, 29 metabolites were found to be significant in urine samples of OC patients and healthy controls (HC). R2Y and Q2 values were found to be 0.8170 and 0.749, respectively. These results showed that the model has high compatibility and predictive power. Benzoic acid, L-threonine, L-pyroglutamic acid, creatinine and 3,4-dihydroxyphenylacetic acid metabolites were determined as prominent biomarkers. The sensitivity of the model was calculated as 93.81% and the specificity as 98.59%. Glycine serine and threonine metabolic pathway, glutathione metabolism and aminoacyl-tRNA biosynthesis pathways were determined important in OC patients and HC. The R2Y, Q2, sensitivity and specificity values in the urine samples of BT patients and HC were found to be 0.869, 0.794, 91.75, 97.01% and 97.18%, respectively. L-threonine, L-pyroglutamic acid, benzoic acid, creatinine and pentadecanol metabolites were determined as prominent biomarkers. Valine, leucine and isoleucine biosynthesis and aminoacyl-tRNA biosynthesis were significant. In this study, thanks to the untargeted metabolomic approach and chemometric methods, every group was differentiated from the others and prominent biomarkers were determined.
引用
收藏
页码:12 / 24
页数:13
相关论文
共 50 条
  • [31] Metabolite Profiling of a NIST Standard Reference Material for Human Plasma (SRM 1950): GC-MS, LC-MS, NMR, and Clinical Laboratory Analyses, Libraries, and Web-Based Resources
    Simon-Manso, Yamil
    Lowenthal, Mark S.
    Kilpatrick, Lisa E.
    Sampson, Maureen L.
    Telu, Kelly H.
    Rudnick, Paul A.
    Mallard, W. Gary
    Bearden, Daniel W.
    Schock, Tracey B.
    Tchekhovskoi, Dmitrii V.
    Blonder, Niksa
    Yan, Xinjian
    Liang, Yuxue
    Zheng, Yufang
    Wallace, William E.
    Neta, Pedatsur
    Phinney, Karen W.
    Remaley, Alan T.
    Stein, Stephen E.
    ANALYTICAL CHEMISTRY, 2013, 85 (24) : 11725 - 11731
  • [32] Metabolic profiles in plasma of patients with herpes labialis based on GC-MS
    Luo, Mengxian
    Guan, Jin-Tao
    Yu, Xiu
    Ding, Yunfei
    Mei, Xian-Xian
    Pan, Xiaoping
    Fan, Yong-Sheng
    Xu, Zheng-Hao
    JOURNAL OF COSMETIC DERMATOLOGY, 2023, 22 (11) : 3152 - 3158
  • [33] Benign serous ovarian tumour: a redefining moment?
    Sally Hunter
    Kylie Gorringe
    Michael Anglesio
    Raghwa Sharma
    Blake Gilks
    Anna deFazio
    David Huntsman
    Ian Campbell
    Hereditary Cancer in Clinical Practice, 10 (Suppl 2)
  • [34] Serous Tubal Intraepithelial Carcinoma and the Dominant Ovarian Mass Clues to Serous Tumor Origin?
    Roh, Michael H.
    Kindelberger, David
    Crum, Christopher P.
    AMERICAN JOURNAL OF SURGICAL PATHOLOGY, 2009, 33 (03) : 376 - 383
  • [35] GC-MS metabolite profiling for specific detection of dwarf somaclonal variation in banana plants
    Cevallos-Cevallos, Juan M.
    Jines, Cristina
    Mariduena-Zavala, Maria G.
    Molina-Miranda, Maria J.
    Ochoa, Daniel E.
    Flores-Cedeno, Jose A.
    APPLICATIONS IN PLANT SCIENCES, 2018, 6 (11):
  • [36] Comparative metabolite fingerprinting of legumes using LC-MS-based untargeted metabolomics
    Llorach, Rafael
    Favari, Claudia
    Alonso, David
    Garcia-Aloy, Mar
    Andres-Lacueva, Cristina
    Urpi-Sarda, Mireia
    FOOD RESEARCH INTERNATIONAL, 2019, 126
  • [37] A potential tool for diagnosis of male infertility: Plasma metabolomics based on GC-MS
    Zhou, Xinyi
    Wang, Yang
    Yun, Yonghuan
    Xia, Zian
    Lu, Hongmei
    Luo, Jiekun
    Liang, Yizeng
    TALANTA, 2016, 147 : 82 - 89
  • [38] Optimal Normalization Method for GC-MS/MS-Based Large-Scale Targeted Metabolomics
    Xue, Liming
    Xu, Jiale
    Feng, Chao
    Lu, Dasheng
    Zhou, Zhijun
    JOURNAL OF ANALYTICAL CHEMISTRY, 2022, 77 (03) : 361 - 368
  • [39] Recent trends in application of chemometric methods for GC-MS and GCxGC-MS-based metabolomic studies
    Feizi, Neda
    Hashemi-Nasab, Fatemeh Sadat
    Golpelichi, Fatemeh
    Saburouh, Nazanin
    Parastar, Hadi
    TRAC-TRENDS IN ANALYTICAL CHEMISTRY, 2021, 138
  • [40] Identification of stably expressed microRNAs in plasma from high-grade serous ovarian carcinoma and benign tumor patients
    Petersen, Patrick H. D.
    Lopacinska-Jorgensen, Joanna
    Hogdall, Claus K.
    Hogdall, Estrid V.
    MOLECULAR BIOLOGY REPORTS, 2023, 50 (12) : 10235 - 10247