–DiagnosticPrognosticPredictive–microRNAmiR-21↑−−3535. J. Wang, F. Che, and J. Zhang, “Cell-free microRNAs as non-invasive biomarkers in glioma: A diagnostic meta-analysis,” Int. J. Biol. Markers 34, 232–242 (2019). https://doi.org/10.1177/1724600819840033, 3636. M. ParvizHamidi et al., “Circulating miR-26a and miR-21 as biomarkers for glioblastoma multiform,” Biotechnol. Appl. Biochem. 66, 261–265 (2019). https://doi.org/10.1002/bab.1707, 3939. Y. Zhang et al., “Prognostic significance of MicroRNAs in glioma: A systematic review and meta-analysis,” Biomed. Res. Int. 2019, 4015969 (2019)., 4141. L. Shi et al., “MiR-21 protected human glioblastoma U87MG cells from chemotherapeutic drug temozolomide induced apoptosis by decreasing Bax/Bcl-2 ratio and caspase-3 activity,” Brain Res. 1352, 255–264 (2010). https://doi.org/10.1016/j.brainres.2010.07.009, 90–9990. Q. Wang et al., “Plasma specific miRNAs as predictive biomarkers for diagnosis and prognosis of glioma,” J. Exp. Clin. Cancer Res. 31, 97 (2012). https://doi.org/10.1186/1756-9966-31-9791. M. Visani et al., “Expression of 19 microRNAs in glioblastoma and comparison with other brain neoplasia of grades I-III,” Mol. Oncol. 8, 417–430 (2014). https://doi.org/10.1016/j.molonc.2013.12.01092. X. Ye et al., “Identification of microRNAs associated with glioma diagnosis and prognosis,” Oncotarget 8, 26394–26403 (2017). https://doi.org/10.18632/oncotarget.1444593. M. Piwecka et al., “Comprehensive analysis of microRNA expression profile in malignant glioma tissues,” Mol. Oncol. 9, 1324–1340 (2015). https://doi.org/10.1016/j.molonc.2015.03.00794. A. Conti et al., “miR-21 and 221 upregulation and miR-181b downregulation in human grade II-IV astrocytic tumors,” J. Neuro-oncol. 93, 325–332 (2009). https://doi.org/10.1007/s11060-009-9797-495. A. Buruiană et al., “The roles of miRNA in glioblastoma tumor cell communication: Diplomatic and aggressive negotiations,” Int. J. Mol. Sci. 21, 1950 (2020). https://doi.org/10.3390/ijms2106195096. J. C. Akers et al., “A cerebrospinal fluid microRNA signature as biomarker for glioblastoma,” Oncotarget 8, 68769–68779 (2017). https://doi.org/10.18632/oncotarget.1833297. C. Li et al., “Prognostic role of microRNA-21 expression in gliomas: A meta-analysis,” J. Neuro-Oncol. 130, 11–17 (2016). https://doi.org/10.1007/s11060-016-2233-798. N. M. Teplyuk et al., “MicroRNAs in cerebrospinal fluid identify glioblastoma and metastatic brain cancers and reflect disease activity,” Neuro-Oncology 14, 689–700 (2012). https://doi.org/10.1093/neuonc/nos07499. P. Ivo D’Urso et al., “miR-15b and miR-21 as circulating biomarkers for diagnosis of glioma,” Curr. Genomics 16, 304–311 (2015). https://doi.org/10.2174/1389202916666150707155610miR-10b↑−−4343. G. Gabriely et al., “Human glioma growth is controlled by microRNA-10b,” Cancer Res. 71, 3563–3572 (2011). https://doi.org/10.1158/0008-5472.CAN-10-3568, 9191. M. Visani et al., “Expression of 19 microRNAs in glioblastoma and comparison with other brain neoplasia of grades I-III,” Mol. Oncol. 8, 417–430 (2014). https://doi.org/10.1016/j.molonc.2013.12.010, 9898. N. M. Teplyuk et al., “MicroRNAs in cerebrospinal fluid identify glioblastoma and metastatic brain cancers and reflect disease activity,” Neuro-Oncology 14, 689–700 (2012). https://doi.org/10.1093/neuonc/nos074, 100100. K. Møllersen, M. Zortea, T. R. Schopf, H. Kirchesch, and F. Godtliebsen, “Comparison of computer systems and ranking criteria for automatic melanoma detection in dermoscopic images,” PLoS One 12, e0190112 (2017). https://doi.org/10.1371/journal.pone.0190112, 101101. C. M. Garcia and S. A. Toms, “The role of circulating MicroRNA in glioblastoma liquid biopsy,” World Neurosurg. 138, 425–435 (2020). https://doi.org/10.1016/j.wneu.2020.03.128miR-155↑−–9393. M. Piwecka et al., “Comprehensive analysis of microRNA expression profile in malignant glioma tissues,” Mol. Oncol. 9, 1324–1340 (2015). https://doi.org/10.1016/j.molonc.2015.03.007, 102102. Y. Zhou et al., “Prognostic role of microRNA-155 expression in gliomas: A meta-analysis,” Clin. Neurol. Neurosurg. 176, 103–109 (2019). https://doi.org/10.1016/j.clineuro.2018.12.005miR-15b↑+–9999. P. Ivo D’Urso et al., “miR-15b and miR-21 as circulating biomarkers for diagnosis of glioma,” Curr. Genomics 16, 304–311 (2015). https://doi.org/10.2174/1389202916666150707155610, 103103. G. Sun et al., “Decreased expression of miR-15b in human gliomas is associated with poor prognosis,” Cancer Biother. Radiopharm. 30, 169–173 (2015)., 104104. C. Yang et al., “Identification of seven serum microRNAs from a genome-wide serum microRNA expression profile as potential noninvasive biomarkers for malignant astrocytomas,” Int. J. Cancer 132, 116–127 (2013). https://doi.org/10.1002/ijc.27657miR-222↑−–3535. J. Wang, F. Che, and J. Zhang, “Cell-free microRNAs as non-invasive biomarkers in glioma: A diagnostic meta-analysis,” Int. J. Biol. Markers 34, 232–242 (2019). https://doi.org/10.1177/1724600819840033, 3838. Y. Song, J. Zhang, M. He, and J. Xu, “Prognostic role of MicroRNA 222 in patients with glioma: A meta-analysis,” Biomed. Res. Int. 2020, 4689689 (2020). https://doi.org/10.1155/2020/4689689, 105105. X. Li, J. Zheng, L. Chen, H. Diao, and Y. Liu, “Predictive and prognostic roles of abnormal expression of tissue miR-125b, miR-221, and miR-222 in glioma,” Mol. Neurobiol. 53, 577–583 (2016). https://doi.org/10.1007/s12035-014-9017-x, 106106. R. Zhang et al., “Plasma miR-221/222 family as novel descriptive and prognostic biomarkers for glioma,” Mol. Neurobiol. 53, 1452–1460 (2016). https://doi.org/10.1007/s12035-014-9079-9miR-221↑−–3939. Y. Zhang et al., “Prognostic significance of MicroRNAs in glioma: A systematic review and meta-analysis,” Biomed. Res. Int. 2019, 4015969 (2019)., 9494. A. Conti et al., “miR-21 and 221 upregulation and miR-181b downregulation in human grade II-IV astrocytic tumors,” J. Neuro-oncol. 93, 325–332 (2009). https://doi.org/10.1007/s11060-009-9797-4, 105–109105. X. Li, J. Zheng, L. Chen, H. Diao, and Y. Liu, “Predictive and prognostic roles of abnormal expression of tissue miR-125b, miR-221, and miR-222 in glioma,” Mol. Neurobiol. 53, 577–583 (2016). https://doi.org/10.1007/s12035-014-9017-x106. R. Zhang et al., “Plasma miR-221/222 family as novel descriptive and prognostic biomarkers for glioma,” Mol. Neurobiol. 53, 1452–1460 (2016). https://doi.org/10.1007/s12035-014-9079-9107. H. G. Møller et al., “A systematic review of MicroRNA in glioblastoma multiforme: Micro-modulators in the mesenchymal mode of migration and invasion,” Mol. Neurobiol. 47, 131–144 (2013). https://doi.org/10.1007/s12035-012-8349-7108. S. A. Ciafrè et al., “Extensive modulation of a set of microRNAs in primary glioblastoma,” Biochem. Biophys. Res. Commun. 334, 1351–1358 (2005). https://doi.org/10.1016/j.bbrc.2005.07.030109. S. Srinivasan, I. R. P. Patric, and K. Somasundaram, “A Ten-microRNA expression signature predicts survival in glioblastoma,” PLoS One 6, e17438 (2011). https://doi.org/10.1371/journal.pone.0017438miR-124↓+3939. Y. Zhang et al., “Prognostic significance of MicroRNAs in glioma: A systematic review and meta-analysis,” Biomed. Res. Int. 2019, 4015969 (2019)., 9292. X. Ye et al., “Identification of microRNAs associated with glioma diagnosis and prognosis,” Oncotarget 8, 26394–26403 (2017). https://doi.org/10.18632/oncotarget.14445, 110110. Z. Shi et al., “MiR-124 governs glioma growth and angiogenesis and enhances chemosensitivity by targeting R-Ras and N-Ras,” Neuro-Oncology 16, 1341–1353 (2014). https://doi.org/10.1093/neuonc/nou084miR-125b↓−+105105. X. Li, J. Zheng, L. Chen, H. Diao, and Y. Liu, “Predictive and prognostic roles of abnormal expression of tissue miR-125b, miR-221, and miR-222 in glioma,” Mol. Neurobiol. 53, 577–583 (2016). https://doi.org/10.1007/s12035-014-9017-x, 111111. X. T. Wei, D. Chen, T. Lv, G. Li, and S. T. Qu, “Serum MicroRNA-125b as a potential biomarker for glioma diagnosis,” Mol. Neurobiol. 53, 163–170 (2016). https://doi.org/10.1007/s12035-014-8993-1miR-7-5p↓112112. L. Dong et al., “miRNA microarray reveals specific expression in the peripheral blood of glioblastoma patients,” Int. J. Oncol. 45, 746–756 (2014). https://doi.org/10.3892/ijo.2014.2459miR-181d↓+4141. L. Shi et al., “MiR-21 protected human glioblastoma U87MG cells from chemotherapeutic drug temozolomide induced apoptosis by decreasing Bax/Bcl-2 ratio and caspase-3 activity,” Brain Res. 1352, 255–264 (2010). https://doi.org/10.1016/j.brainres.2010.07.009, 4444. W. Zhang et al., “MiR-181d: Predictive glioblastoma biomarker that downregulates MGMT expression,” Neuro-Oncology 14, 712–719 (2012). https://doi.org/10.1093/neuonc/nos089–––––Extracellular vesiclesEGFRvIII protein=/↑−–51–5351. J. M. Figueroa et al., “Detection of wild-type EGFR amplification and EGFRvIII mutation in CSF-derived extracellular vesicles of glioblastoma patients,” Neuro-Oncology 19, 1494–1502 (2017). https://doi.org/10.1093/neuonc/nox08552. J. Skog et al., “Glioblastoma microvesicles transport RNA and proteins that promote tumour growth and provide diagnostic biomarkers,” Nat. Cell Biol. 10, 1470–1476 (2008). https://doi.org/10.1038/ncb180053. H. Shao et al., “Protein typing of circulating microvesicles allows real-time monitoring of glioblastoma therapy,” Nat. Med. 18, 1835–1840 (2012). https://doi.org/10.1038/nm.2994, 5555. B. D. Choi et al., “EGFRvIII-targeted vaccination therapy of malignant glioma,” Brain Pathol. 19, 713–723 (2009). https://doi.org/10.1111/j.1750-3639.2009.00318.x, 113113. H. Johnson et al., “Molecular characterization of EGFR and EGFRvIII signaling networks in human glioblastoma tumor xenografts,” Mol. Cell. Proteomics 11, 1724–1740 (2012). https://doi.org/10.1074/mcp.M112.019984CD44↑−–57–6057. D. Choi et al., “The impact of oncogenic EGFRvIII on the proteome of extracellular vesicles released from glioblastoma cells,” Mol. Cell. Proteomics 17, 1948–1964 (2018). https://doi.org/10.1074/mcp.RA118.00064458. S. Misra et al., “Hyaluronan-CD44 interactions as potential targets for cancer therapy,” FEBS J. 278, 1429–1443 (2011). https://doi.org/10.1111/j.1742-4658.2011.08071.x59. T. Yoshida, Y. Matsuda, Z. Naito, and T. Ishiwata, “CD44 in human glioma correlates with histopathological grade and cell migration,” Pathol. Int. 62, 463–470 (2012). https://doi.org/10.1111/j.1440-1827.2012.02823.x60. Y. Akiyama et al., “Hyaluronate receptors mediating glioma cell migration and proliferation,” J. Neuro-Oncol. 53, 115–127 (2001). https://doi.org/10.1023/A:1012297132047, 114–117114. M. M. Knüpfer et al., “CD44 expression and hyaluronic acid binding of malignant glioma cells,” Clin. Exp. Metastasis 17, 81–86 (1999). https://doi.org/10.1023/A:1026425519497115. D. V. Brown et al., “Expression of CD133 and CD44 in glioblastoma stem cells correlates with cell proliferation, phenotype stability and intratumor heterogeneity,” PLoS One 12, e0172791 (2017). https://doi.org/10.1371/journal.pone.0172791116. Q. Dong et al., “Elevated CD44 expression predicts poor prognosis in patients with low-grade glioma,” Oncol. Lett. 18, 3698–3704 (2019).117. C. Hou et al., “Overexpression of CD44 is associated with a poor prognosis in grade II/III gliomas,” J. Neurooncol. 145, 201–210 (2019). https://doi.org/10.1007/s11060-019-03288-8CD133↑−–115115. D. V. Brown et al., “Expression of CD133 and CD44 in glioblastoma stem cells correlates with cell proliferation, phenotype stability and intratumor heterogeneity,” PLoS One 12, e0172791 (2017). https://doi.org/10.1371/journal.pone.0172791, 118118. W. Zhang, H. Chen, S. Lv, and H. Yang, “High CD133 expression is associated with worse prognosis in patients with glioblastoma,” Mol. Neurobiol. 53, 2354–2360 (2016). https://doi.org/10.1007/s12035-015-9187-1TGFB1↑−–5656. S. K. Guo, M. F. Shen, H. W. Yao, and Y. S. Liu, “Enhanced expression of TGFBI promotes the proliferation and migration of glioma cells,” Cell. Physiol. Biochem. 49, 1097–1109 (2018)., 5757. D. Choi et al., “The impact of oncogenic EGFRvIII on the proteome of extracellular vesicles released from glioblastoma cells,” Mol. Cell. Proteomics 17, 1948–1964 (2018). https://doi.org/10.1074/mcp.RA118.000644, 119119. I. Bryukhovetskiy and V. Shevchenko, “Molecular mechanisms of the effect of TGF-β1 on U87 human glioblastoma cells,” Oncol. Lett. 12, 1581–1590 (2016). https://doi.org/10.3892/ol.2016.4756, 120120. B. Kaminska, M. Kocyk, and M. Kijewska, “TGF beta signaling and its role in glioma pathogenesis,” Adv. Exp. Med. Biol. 986, 171–187 (2013). https://doi.org/10.1007/978-94-007-4719-7_9MCT1↑−–121–124121. A. P. Halestrap, “The monocarboxylate transporter family-structure and functional characterization,” IUBMB Life 64, 1–9 (2012). https://doi.org/10.1002/iub.573122. C. B. Colen et al., “Metabolic targeting of lactate efflux by malignant glioma inhibits invasiveness and induces necrosis: An in vivo study,” Neoplasia 13, 620–632 (2011). https://doi.org/10.1593/neo.11134123. V. Miranda-Gonçalves et al., “Hypoxia-mediated upregulation of MCT1 expression supports the glycolytic phenotype of glioblastomas,” Oncotarget 7, 46335–46353 (2016). https://doi.org/10.18632/oncotarget.10114124. A. Thakur et al., “Label-free sensing of exosomal MCT1 and CD147 for tracking metabolic reprogramming and malignant progression in glioma,” Sci. Adv. 6, eaaz6119 (2020). https://doi.org/10.1126/sciadv.aaz6119MCT4↑−–125125. N. W. Colangelo and E. I. Azzam, “Extracellular vesicles originating from glioblastoma cells increase metalloproteinase release by astrocytes: The role of CD147 (EMMPRIN) and ionizing radiation,” Cell Commun. Sign. 18, 21 (2020). https://doi.org/10.1186/s12964-019-0494-4, 126126. S. W. Lai, H. J. Lin, Y. S. Liu, L. Y. Yang, and D. Y. Lu, “Monocarboxylate transporter 4 regulates glioblastoma motility and monocyte binding ability,” Cancers 12, 380 (2020). https://doi.org/10.3390/cancers12020380–––––ProteinsGFAP↑–63–6663. J. G. Pérez-Larraya et al., “Diagnostic and prognostic value of preoperative combined GFAP, IGFBP-2, and YKL-40 plasma levels in patients with glioblastoma,” Cancer 120, 3972–3980 (2014). https://doi.org/10.1002/cncr.2894964. J. Tichy et al., “Prospective evaluation of serum glial fibrillary acidic protein (GFAP) as a diagnostic marker for glioblastoma,” J. Neuro-Oncol. 126, 361–369 (2015). https://doi.org/10.1007/s11060-015-1978-865. C. S. Jung et al., “Serum GFAP is a diagnostic marker for glioblastoma multiforme,” Brain 130, 3336–3341 (2007). https://doi.org/10.1093/brain/awm26366. A. Kiviniemi et al., “Serum levels of GFAP and EGFR in primary and recurrent high-grade gliomas: Correlation to tumor volume, molecular markers, and progression-free survival,” J. Neuro-Oncol. 124, 237–245 (2015). https://doi.org/10.1007/s11060-015-1829-7VEGF↑−–70–7270. F. Shen et al., “Proteomic analysis of cerebrospinal fluid: Toward the identification of biomarkers for gliomas,” Neurosurg. Rev. 37, 367–380 (2014). https://doi.org/10.1007/s10143-014-0539-571. F. W. Khwaja et al., “Proteomic identification of biomarkers in the cerebrospinal fluid (CSF) of astrocytoma patients,” J. Proteome Res. 6, 559–570 (2007). https://doi.org/10.1021/pr060240z72. P. Sampath et al., “Cerebrospinal fluid (vascular endothelial growth factor) and serologic (recoverin) tumor markers for malignant glioma,” Cancer Control 11, 174–180 (2004). https://doi.org/10.1177/107327480401100305YKL-40↑−–6363. J. G. Pérez-Larraya et al., “Diagnostic and prognostic value of preoperative combined GFAP, IGFBP-2, and YKL-40 plasma levels in patients with glioblastoma,” Cancer 120, 3972–3980 (2014). https://doi.org/10.1002/cncr.28949, 67–6967. N. A. Schultz and J. S. Johansen, “YKL-40-a protein in the field of translational medicine: A role as a biomarker in cancer patients?,” Cancers 2, 1453–1491 (2010). https://doi.org/10.3390/cancers203145368. G. Qin et al., “Prognostic value of YKL-40 in patients with glioblastoma: A systematic review and meta-analysis,” Mol. Neurobiol. 54, 3264–3270 (2017). https://doi.org/10.1007/s12035-016-9878-269. D. Bernardi et al., “Serum YKL-40 following resection for cerebral glioblastoma,” J. Neuro-Oncol 107, 299–305 (2012). https://doi.org/10.1007/s11060-011-0762-7, 127127. A. Hormigo et al., “YKL-40 and matrix metalloproteinase-9 as potential serum biomarkers for patients with high-grade gliomas,” Clin. Cancer Res. 12, 5698–5704 (2006). https://doi.org/10.1158/1078-0432.CCR-06-0181–––––Circulatory tumor DNAEGFR amplification=/↑−–2828. A. M. Miller et al., “Tracking tumour evolution in glioma through liquid biopsies of cerebrospinal fluid,” Nature 565, 654–658 (2019). https://doi.org/10.1038/s41586-019-0882-3, 5151. J. M. Figueroa et al., “Detection of wild-type EGFR amplification and EGFRvIII mutation in CSF-derived extracellular vesicles of glioblastoma patients,” Neuro-Oncology 19, 1494–1502 (2017). https://doi.org/10.1093/neuonc/nox085, 5252. J. Skog et al., “Glioblastoma microvesicles transport RNA and proteins that promote tumour growth and provide diagnostic biomarkers,” Nat. Cell Biol. 10, 1470–1476 (2008). https://doi.org/10.1038/ncb1800, 8181. L. de Mattos-Arruda et al., “Cerebrospinal fluid-derived circulating tumour DNA better represents the genomic alterations of brain tumours than plasma,” Nat. Commun. 6, 8839 (2015). https://doi.org/10.1038/ncomms9839MGMT promoter methylation=/↑−–76–8076. I. Lavon, M. Refael, B. Zelikovitch, E. Shalom, and T. Siegal, “Serum DNA can define tumor-specific genetic and epigenetic markers in gliomas of various grades,” Neuro-Oncology 12, 173–180 (2010). https://doi.org/10.1093/neuonc/nop04177. C. Balañá et al., “Tumour and serum MGMT promoter methylation and protein expression in glioblastoma patients,” Clin. Transl. Oncol. 13, 677–685 (2011). https://doi.org/10.1007/s12094-011-0714-x78. A. Majchrzak-Celińska et al., “Detection of MGMT, RASSF1A, p15INK4B, and p14ARF promoter methylation in circulating tumor-derived DNA of central nervous system cancer patients,” J. Appl. Genet. 54, 335–344 (2013). https://doi.org/10.1007/s13353-013-0149-x79. J. L. Ramirez et al., “Serum DNA as a tool for cancer patient management,” Rocz. Akad. Med. Bialymst. 48, 34–41 (2003).80. K. D. Weaver, S. A. Grossman, and J. G. Herman, “Methylated tumor-specific DNA as a plasma biomarker in patients with glioma,” Cancer Invest. 24, 35–40 (2006). https://doi.org/10.1080/07357900500449546IDH1 mutation=/↑−–2828. A. M. Miller et al., “Tracking tumour evolution in glioma through liquid biopsies of cerebrospinal fluid,” Nature 565, 654–658 (2019). https://doi.org/10.1038/s41586-019-0882-3, 81–8381. L. de Mattos-Arruda et al., “Cerebrospinal fluid-derived circulating tumour DNA better represents the genomic alterations of brain tumours than plasma,” Nat. Commun. 6, 8839 (2015). https://doi.org/10.1038/ncomms983982. B. Boisselier et al., “Detection of IDH1 mutation in the plasma of patients with glioma,” Neurology 79, 1693–1698 (2012). https://doi.org/10.1212/WNL.0b013e31826e9b0a83. S. Nobusawa, T. Watanabe, P. Kleihues, and H. Ohgaki, “IDH1 mutations as molecular signature and predictive factor of secondary glioblastomas,” Clin. Cancer Res. 15, 6002–6007 (2009). https://doi.org/10.1158/1078-0432.CCR-09-07151p/19q codeletion=/↑−–2828. A. M. Miller et al., “Tracking tumour evolution in glioma through liquid biopsies of cerebrospinal fluid,” Nature 565, 654–658 (2019). https://doi.org/10.1038/s41586-019-0882-3, 7676. I. Lavon, M. Refael, B. Zelikovitch, E. Shalom, and T. Siegal, “Serum DNA can define tumor-specific genetic and epigenetic markers in gliomas of various grades,” Neuro-Oncology 12, 173–180 (2010). https://doi.org/10.1093/neuonc/nop041–––––MetabolitesGlutamate↑–+8888. J. de Groot and H. Sontheimer, “Glutamate and the biology of gliomas,” Glia 59, 1181–1189 (2011). https://doi.org/10.1002/glia.21113, 8989. J. S. So, H. Kim, and K. S. Han, “Mechanisms of invasion in glioblastoma: Extracellular matrix, Ca2+ signaling, and glutamate,” Front. Cell. Neurosci. 15, 663092 (2021). https://doi.org/10.3389/fncel.2021.663092, 128–130128. H. Nagashima et al., “Diagnostic value of glutamate with 2-hydroxyglutarate in magnetic resonance spectroscopy for IDH1 mutant glioma,” Neuro-Oncology 18, 1559–1568 (2016).129. E. Subramani et al., “Glutamate is a noninvasive metabolic biomarker of IDH1-mutant glioma response to temozolomide treatment,” Cancer Res. 80, 5098–510 (2020). https://doi.org/10.1158/0008-5472.CAN-20-1314130. M. Radoul et al., “Early noninvasive metabolic biomarkers of mutant idh inhibition in glioma,” Metabolites 11, 109 (2021). https://doi.org/10.3390/metabo11020109Cysteine↑–8585. W. J. Chung et al., “Inhibition of cystine uptake disrupts the growth of primary brain tumors,” J. Neurosci. 25, 7101–7110 (2005). https://doi.org/10.1523/JNEUROSCI.5258-04.2005, 8787. L. Mörén et al., “Metabolomic screening of tumor tissue and serum in glioma patients reveals diagnostic and prognostic information,” Metabolites 5, 502–520 (2015). https://doi.org/10.3390/metabo5030502