ORIGINAL RESEARCH
New non-invasive approaches to the diagnosis of lymph node metastases from breast cancer by mass spectrometry
1 Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology, Moscow, Russia
2 V. L. Talrose Institute for Energy Problems of Chemical Physics, Moscow, Russia
Correspondence should be addressed: Vladimir E. Frankevich
Oparina, 4, Moscow, 117997, Russia; moc.liamg@hciveknarfv
Funding: the study was funded by RFBR and National Natural Science Foundation of China within the framework of the scientific project № 19-515-55021
Compliance with ethical standards: the study was approved by the Ethics Committee of Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology (protocol № 9 dated November 22, 2018); the study was carried out in accordance with the requirements of the Declaration of Helsinki, International Council for Harmonisation (ICF), Good Clinical Practice (GCP) guidelines, Federal Law 323-FZ dated November 21, 2011 “On the Basics of Protecting the Health of Citizens in the Russian Federation”; the informed consent was submitted by all patients.
- Fidler IJ. The pathogenesis of cancer metastasis: the ‘seed and soil’ hypothesis revisited. Nat Rev Cancer. 2003; 3 (6): 453–8.
- Silberman AW, McVay C, Cohen JS, Altura JF, Brackert S, Sarna GP, et al. Comparative Morbidity of Axillary Lymph Node Dissection and the Sentinel Lymph Node Technique. Ann Surg. 2004; 240 (1): 1–6.
- Schrenk P, Rieger R, Shamiyeh A, Wayand W. Morbidity following sentinel lymph node biopsy versus axillary lymph node dissection for patients with breast carcinoma. Cancer. 2000; 88 (3): 608–14.
- Sukhikh GT, Sencha AN. Multiparametric ultrasound diagnosis of breast diseases. Cham: Springer, 2018.
- Zhou M, Lu B, Lv G, Tang Q, Zhu J, Li J, et al. Differential diagnosis between metastatic and non-metastatic lymph nodes using DWMRI: a meta-analysis of diagnostic accuracy studies. J Cancer Res Clin Oncol. 2015; 141 (6): 1119–30.
- Wang T, Xiao S, Liu Y, Lin Z, Su N, Li X, et al. The efficacy of plasma biomarkers in early diagnosis of Alzheimer’s disease. Int J Geriatr Psychiatry. 2014; 29 (7): 713–9.
- Lin YW, Lai HC, Lin CY, Chiou JY, Shui HA, Chang CC, et al. Plasma proteomic profiling for detecting and differentiating in situ and invasive carcinomas of the uterine cervix. Int J Gynecol Cancer. 2006; 16 (3): 1216–24.
- Zhong L, Coe SP, Stromberg AJ, Khattar NH, Jett JR, Hirschowitz EA. Profiling tumor-associated antibodies for early detection of nonsmall cell lung cancer. J Thorac Oncol. 2006; 1 (6): 513–9.
- Schwarz KB, Rosensweig J, Sharma S, Jones L, Durant M, Potter C, et al. Plasma markers of platelet activation in cystic fibrosis liver and lung disease. J Pediatr Gastroenterol Nutr. 2003; 37 (2): 187–91.
- Langenskiöld M, Holmdahl L, Falk P, Ivarsson ML. Increased plasma MMP-2 protein expression in lymph node-positive patients with colorectal cancer. Int J Colorectal Dis. 2005; 20 (3): 245–52.
- Chai YD, Zhang L, Yang Y, Su T. Discovery of potential serum protein biomarkers for lymph-node metastasis in oral cancer. Head Neck. 2015; 38 (1): 118–25.
- Yigitbasi T, Calibasi-Kocal G, Buyukuslu N, Kemal Atahan M, Kupeli H, Yigit S, et al. SELDI-TOF-MS Profiling of Metastatic Phenotype in Histopathological Subtypes of Breast Cancer. Curr Proteomics. 2018; 15 (3): 214–20.
- Bandu R, Mok HJ, Kim KP. Phospholipids as cancer biomarkers: mass spectrometry-based analysis. Mass Spectrom Rev. 2016; 47 (3): 1–32.
- Chen X, Chen H, Dai M, Ai J, Li Y, Mahon B, et al. Plasma lipidomics profiling identified lipid biomarkers in distinguishing early-stage breast cancer from benign lesions. Oncotarget. 2016; 7 (24): 36622–31.
- Folch J, Lees M, Sloane Stanley GH. A simple method for the isolation and purification of total lipides from animal tissues. J Biol Chem. 1957; 226 (1): 497–509.
- Koelmel JP, Kroeger NM, Ulmer CZ, Bowden JA, Patterson RE, Cochran JA, et al. LipidMatch: An automated workflow for rulebased lipid identification using untargeted high-resolution tandem mass spectrometry data. BMC Bioinformatics. 2017; 18 (1): 1–11.
- R Development Core Team. A Language and Environment for Statistical Computing. R Found Stat Comput. 2019.
- R team. R Studio: Integrated Development for R. 2016.
- Galindo-Prieto B, Eriksson L, Trygg J. Variable influence on projection (VIP) for OPLS models and its applicability in multivariate time series analysis. Chemom Intell Lab Syst. 2015; 146: 297–304.
- Akaike H. A New Look at the Statistical Model Identification. IEEE Trans Automat Contr. 1974; 19 (6): 716–23.
- Miller YI, Shyy JYJ. Context-Dependent Role of Oxidized Lipids and Lipoproteins in Inflammation. Trends Endocrinol Metab. 2017; 28 (2): 143–52.
- Paynter NP, Balasubramanian R, Giulianini F, Wang DD, Tinker LF, Gopal S etc. Metabolic predictors of incident coronary heart disease in women. Circulation. 2018; 137 (8): 841–53.
- Ferreri C, Sansone A, Ferreri R, Amézaga J, Tueros I. Fatty acids and membrane lipidomics in oncology: A cross-road of nutritional, signaling and metabolic pathways. Metabolites. 2020; 10 (9): 1–26.
- Maan M, Peters JM, Dutta M, Patterson AD. Lipid metabolism and lipophagy in cancer. Biochem Biophys Res Commun. 2018; 504 (3): 582–9.
- Kus K, Kij A, Zakrzewska A, Jasztal A, Stojak M, Walczak M, et al. Alterations in arginine and energy metabolism, structural and signalling lipids in metastatic breast cancer in mice detected in plasma by targeted metabolomics and lipidomics. Breast Cancer Res. 2018; 20 (1): 1–13.
- Tokareva AO, Chagovets VV, Rodionov VV, Kometova VV, Rodionova MV, Starodubtseva NL, i dr. Lipidnye markery metastaticheskogo porazhenija regionarnyh limfouzlov u bol'nyh rakom molochnoj zhelezy. Akusherstvo i ginekologija. 2020; 8: 133–40. Russia.