2,175
Views
3
CrossRef citations to date
0
Altmetric
Research Article

Standardized uptake value (SUVmax) in 18F-FDG PET/CT is correlated with the total number of main oncogenic anomalies in cancer patients

ORCID Icon, , ORCID Icon &
Pages 1067-1071 | Received 21 Oct 2019, Accepted 24 Sep 2020, Published online: 01 Nov 2020

References

  • Vogelstein B, Papadopoulos N, Velculescu VE, Zhou S, Diaz LA, Kinzler KW. Cancer genome landscapes. Science. 2013;339:1546–1558.
  • Mazurowski MA. Radiogenomics: what it is and why it is important. J Am Coll Radiol. 2015;12:862–866. doi:10.1016/j.jacr.2015.04.019.
  • Jansen RW, van Amstel P, Martens RM, Kooi IE, Wesseling P, de Langen AJ, Menke-van der Houven van Oordt CW, Jansen BHE, Moll AC, Dorsman JC, et al. Non-invasive tumor genotyping using radiogenomic biomarkers, a systematic review and oncology-wide pathway analysis. Oncotarget. 2018;9(28):20134–20155. doi:10.18632/oncotarget.24893.
  • Dhingra VK, Mahajan A, Basu S. Emerging clinical applications of PET based molecular imaging in oncology: the promising future potential for evolving personalized cancer care. Indian J Radiol Imaging. 2015;25:332–341. doi:10.4103/0971-3026.169467.
  • Lee JW, Lee SM. Radiomics in oncological PET/CT: clinical applications. Nucl Med Mol Imaging. 2018;52:170–189. doi:10.1007/s13139-017-0500-y.
  • Suárez-Piñera M, Belda-Sanchis J, Taus A, Sánchez-Font A, Mestre-Fusco A, Jiménez M, Pijuan L. FDG PET-CT SUVmax and IASLC/ATS/ERS histologic classification: a new profile of lung adenocarcinoma with prognostic value. Am J Nucl Med Mol Imaging. 2018;8:100–109
  • Heiden BT, Chen G, Hermann M, Brown RKJ, Orringer MB, Lin J, Chang AC, Carrott PW, Lynch WR, Zhao L, et al. 18F-FDG PET intensity correlates with a hypoxic gene signature and other oncogenic abnormalities in operable non-small cell lung cancer. PLoS One. 2018;13(7):e0199970. doi:10.1371/journal.pone.0199970.
  • Nair VS, Gevaert O, Davidzon G, Napel S, Graves EE, Hoang CD, Shrager JB, Quon A, Rubin DL, Plevritis SK, et al. Prognostic PET 18F-FDG uptake imaging features are associated with major oncogenomic alterations in patients with resected non-small cell lung cancer. Cancer Res. 2012;72(15):3725–3734. doi:10.1158/0008-5472.CAN-11-3943.
  • Caicedo C, Garcia-Velloso MJ, Lozano MD, Labiano T, Vigil Diaz C, Lopez-Picazo JM, Gurpide A, Zulueta J, Richter Echevarria JA, Perez Gracia JL, et al. Role of [1⁸F]FDG PET in prediction of KRAS and EGFR mutation status in patients with advanced non-small-cell lung cancer. Eur J Nucl Med Mol Imaging. 2014;41:2058–2065. doi:10.1007/s00259-014-2833-4.
  • Chalmers ZR, Connelly CF, Fabrizio D, Gay L, Ali SM, Ennis R, Schrock A, Campbell B, Shlien A, Chmielecki J, et al. Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden. Genome Med. 2017;9(1):34. doi:10.1186/s13073-017-0424-2.
  • Ock CY, Hwang JE, Keam B, Kim SB, Shim JJ, Jang HJ, et al. Genomic landscape associated with potential response to anti-CTLA-4 treatment in cancers. Nat Commun. 2017;8:1050.
  • Ahn KS, Kang KJ, Kim YH, Kim TS, Song BI, Kim HW, O’Brien D, Roberts LR, Lee JW, Won KS, et al. Genetic features associated with 18F-FDG uptake in intrahepatic cholangiocarcinoma. Ann Surg Treat Res. 2019;96:153–161. doi:10.4174/astr.2019.96.4.153.
  • Chang GH, Kurzrock R, Tran L, Schwaederle M, Hoh CK. mutations and number of alterations correlate with maximum standardized uptake value (SUVmax) determined by positron emission tomography/computed tomography (PET/CT). Oncotarget. 2018;9:14306–14310.
  • Choi H, Na KJ. Pan-cancer analysis of tumor metabolic landscape associated with genomic alterations. Mol Cancer. 2018;17:150. doi:10.1186/s12943-018-0895-9.
  • Ghasemi M, Nabipour I, Omrani A, Alipour Z, Assadi M. Precision medicine and molecular imaging: new targeted approaches toward cancer therapeutic and diagnosis. Am J Nucl Med Mol Imaging. 2016;6:310–327.
  • Vaidya T, Agrawal A, Mahajan S, Thakur MH, Mahajan A. The continuing evolution of molecular functional imaging in clinical oncology: the road to precision medicine and radiogenomics (Part I). Mol Diagn Ther. 2019;23:1–26. doi:10.1007/s40291-018-0366-4.
  • Hay N. Reprogramming glucose metabolism in cancer: can it be exploited for cancer therapy? Nat Rev Cancer. 2016;16:635–649. doi:10.1038/nrc.2016.77.
  • Granja S, Pinheiro C, Reis RM, Martinho O, Baltazar F. Glucose addiction in cancer therapy: advances and drawbacks. Curr Drug Metab. 2015;16:221–242.