Potential Utility of FDG PET-CT as a Non-invasive Tool for Monitoring Local Immune Responses

  • Lee, Seungho (Department of Surgery, Yonsei University College of Medicine, Yonsei University Health System) ;
  • Choi, Seohee (Department of Surgery, Yonsei University College of Medicine, Yonsei University Health System) ;
  • Kim, Sang Yong (Medical Research Center, Yonsei University College of Medicine) ;
  • Yun, Mi Jin (Department of Nuclear Medicine, Yonsei University College of Medicine) ;
  • Kim, Hyoung-Il (Department of Surgery, Yonsei University College of Medicine, Yonsei University Health System)
  • Received : 2017.12.19
  • Accepted : 2017.12.22
  • Published : 2017.12.31


Purpose: The tumor microenvironment is known to be associated with the metabolic activity of cancer cells and local immune reactions. We hypothesized that glucose metabolism measured by 2-deoxy-2-($^{18}F$)fluoro-D-glucose ($^{18}F-FDG$) positron emission tomography (PET)-computed tomography (CT) ($^{18}F-FDG$ PET-CT) would be associated with local immune responses evaluated according to the presence of tumor infiltrating lymphocytes (TILs). Materials and Methods: We retrospectively reviewed 56 patients who underwent $^{18}F-FDG$ PET-CT prior to gastrectomy. In resected tumor specimens, TIL subsets, including cluster of differentiation (CD) 3, CD4, CD8, Forkhead box P3 (Foxp3), and granzyme B, were subjected to immunohistochemical analysis. The prognostic nutritional index (PNI) was calculated as: ($10{\times}serum$ albumin value)+($0.005{\times}peripheral$ lymphocyte counts). Additionally, the maximum standard uptake value ($SUV_{max}$) was calculated to evaluate the metabolic activity of cancer cells. Results: The $SUV_{max}$ was positively correlated with larger tumor size (R=0.293; P=0.029) and negatively correlated with PNI (R=-0.407; P=0.002). A higher $SUV_{max}$ showed a marginal association with higher CD3 (+) T lymphocyte counts (R=0.227; P=0.092) and a significant association with higher Foxp3 (+) T lymphocyte counts (R=0.431; P=0.009). No other clinicopathological characteristics were associated with $SUV_{max}$ or TILs. Survival analysis, however, indicated that neither $SUV_{max}$ nor Foxp3 held prognostic significance. Conclusions: FDG uptake on PET-CT could be associated with TILs, especially regulatory T cells, in gastric cancer. This finding may suggest that PET-CT could be of use as a non-invasive tool for monitoring the tumor microenvironment in patients with gastric cancer.


Supported by : National Research Foundation of Korea (NRF)


  1. Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-Tieulent J, Jemal A. Global cancer statistics, 2012. CA Cancer J Clin 2015;65:87-108.
  2. Shiraishi N, Inomata M, Osawa N, Yasuda K, Adachi Y, Kitano S. Early and late recurrence after gastrectomy for gastric carcinoma. Univariate and multivariate analyses. Cancer 2000;89:255-261.<255::AID-CNCR8>3.0.CO;2-N
  3. Bomanji JB, Costa DC, Ell PJ. Clinical role of positron emission tomography in oncology. Lancet Oncol 2001;2:157-164.
  4. Huang Y, Feng M, He Q, Yin J, Xu P, Jiang Q, et al. Prognostic value of pretreatment 18F-FDG PET-CT for nasopharyngeal carcinoma patients. Medicine (Baltimore) 2017;96:e6721.
  5. Kim YH, Lee JA, Baek JM, Sung GY, Lee DS, Won JM. The clinical significance of standardized uptake value in breast cancer measured using 18F-fluorodeoxyglucose positron emission tomography/computed tomography. Nucl Med Commun 2015;36:790-794.
  6. Pauwels EK, Ribeiro MJ, Stoot JH, McCready VR, Bourguignon M, Maziere B. FDG accumulation and tumor biology. Nucl Med Biol 1998;25:317-322.
  7. Ott K, Fink U, Becker K, Stahl A, Dittler HJ, Busch R, et al. Prediction of response to preoperative chemotherapy in gastric carcinoma by metabolic imaging: results of a prospective trial. J Clin Oncol 2003;21:4604-4610.
  8. Yun M. Imaging of gastric cancer metabolism using 18 F-FDG PET/CT. J Gastric Cancer 2014;14:1-6.
  9. Dassen AE, Lips DJ, Hoekstra CJ, Pruijt JF, Bosscha K. FDG-PET has no definite role in preoperative imaging in gastric cancer. Eur J Surg Oncol 2009;35:449-455.
  10. Song BI, Kim HW, Won KS, Ryu SW, Sohn SS, Kang YN. Preoperative standardized uptake value of metastatic lymph nodes measured by 18F-FDG PET/CT improves the prediction of prognosis in gastric cancer. Medicine (Baltimore) 2015;94:e1037.
  11. Wu Z, Zhao J, Gao P, Song Y, Sun J, Chen X, et al. Prognostic value of pretreatment standardized uptake value of F-18-fluorodeoxyglucose PET in patients with gastric cancer: a meta-analysis. BMC Cancer 2017;17:275.
  12. Park JC, Lee JH, Cheoi K, Chung H, Yun MJ, Lee H, et al. Predictive value of pretreatment metabolic activity measured by fluorodeoxyglucose positron emission tomography in patients with metastatic advanced gastric cancer: the maximal SUV of the stomach is a prognostic factor. Eur J Nucl Med Mol Imaging 2012;39:1107-1116.
  13. Hui L, Chen Y. Tumor microenvironment: Sanctuary of the devil. Cancer Lett 2015;368:7-13.
  14. Cairns RA, Harris IS, Mak TW. Regulation of cancer cell metabolism. Nat Rev Cancer 2011;11:85-95.
  15. Kaira K, Serizawa M, Koh Y, Takahashi T, Yamaguchi A, Hanaoka H, et al. Biological significance of 18F-FDG uptake on PET in patients with non-small-cell lung cancer. Lung Cancer 2014;83:197-204.
  16. Takebayashi R, Izuishi K, Yamamoto Y, Kameyama R, Mori H, Masaki T, et al. [18F]Fluorodeoxyglucose accumulation as a biological marker of hypoxic status but not glucose transport ability in gastric cancer. J Exp Clin Cancer Res 2013;32:34.
  17. van Baardwijk A, Dooms C, van Suylen RJ, Verbeken E, Hochstenbag M, Dehing-Oberije C, et al. The maximum uptake of (18)F-deoxyglucose on positron emission tomography scan correlates with survival, hypoxia inducible factor-1alpha and GLUT-1 in non-small cell lung cancer. Eur J Cancer 2007;43:1392-1398.
  18. Clambey ET, McNamee EN, Westrich JA, Glover LE, Campbell EL, Jedlicka P, et al. Hypoxia-inducible factor-1 alpha-dependent induction of FoxP3 drives regulatory T-cell abundance and function during inflammatory hypoxia of the mucosa. Proc Natl Acad Sci U S A 2012;109:E2784-E2793.
  19. Deng B, Zhu JM, Wang Y, Liu TT, Ding YB, Xiao WM, et al. Intratumor hypoxia promotes immune tolerance by inducing regulatory T cells via $TGF-{\beta}1$ in gastric cancer. PLoS One 2013;8:e63777.
  20. Kumar V, Gabrilovich DI. Hypoxia-inducible factors in regulation of immune responses in tumour microenvironment. Immunology 2014;143:512-519.
  21. Clemente CG, Mihm MC Jr, Bufalino R, Zurrida S, Collini P, Cascinelli N. Prognostic value of tumor infiltrating lymphocytes in the vertical growth phase of primary cutaneous melanoma. Cancer 1996;77:1303-1310.<1303::AID-CNCR12>3.0.CO;2-5
  22. Kim HI, Kim H, Cho HW, Kim SY, Song KJ, Hyung WJ, et al. The ratio of intra-tumoral regulatory T cells (Foxp3+)/helper T cells (CD4+) is a prognostic factor and associated with recurrence pattern in gastric cardia cancer. J Surg Oncol 2011;104:728-733.
  23. Zhuang Y, Peng LS, Zhao YL, Shi Y, Mao XH, Guo G, et al. Increased intratumoral IL-22-producing CD4(+) T cells and Th22 cells correlate with gastric cancer progression and predict poor patient survival. Cancer Immunol Immunother 2012;61:1965-1975.
  24. Peng LS, Zhuang Y, Shi Y, Zhao YL, Wang TT, Chen N, et al. Increased tumor-infiltrating CD8(+)Foxp3(+) T lymphocytes are associated with tumor progression in human gastric cancer. Cancer Immunol Immunother 2012;61:2183-2192.
  25. Choi HS, Ha SY, Kim HM, Ahn SM, Kang MS, Kim KM, et al. The prognostic effects of tumor infiltrating regulatory T cells and myeloid derived suppressor cells assessed by multicolor flow cytometry in gastric cancer patients. Oncotarget 2016;7:7940-7951.
  26. Kim KJ, Lee KS, Cho HJ, Kim YH, Yang HK, Kim WH, et al. Prognostic implications of tumor-infiltrating FoxP3+ regulatory T cells and CD8+ cytotoxic T cells in microsatellite-unstable gastric cancers. Hum Pathol 2014;45:285-293.
  27. Fischer K, Hoffmann P, Voelkl S, Meidenbauer N, Ammer J, Edinger M, et al. Inhibitory effect of tumor cell-derived lactic acid on human T cells. Blood 2007;109:3812-3819.
  28. Chang CH, Qiu J, O'Sullivan D, Buck MD, Noguchi T, Curtis JD, et al. Metabolic competition in the tumor microenvironment is a driver of cancer progression. Cell 2015;162:1229-1241.
  29. Stomach. In: Compton CC, Byrd DR, Garcia-Aguilar J, Kurtzman SH, Olawaiye A, Washington MK, eds. AJCC Cancer Staging Atlas: a Companion to the Seventh Editions of the AJCC Cancer Staging Manual and Handbook. 2nd ed. New York (NY): Springer, 2012:143-153.
  30. Lee JY, Kim HI, Kim YN, Hong JH, Alshomimi S, An JY, et al. Clinical significance of the prognostic nutritional index for predicting short- and long-term surgical outcomes after gastrectomy: a retrospective analysis of 7781 gastric cancer patients. Medicine (Baltimore) 2016;95:e3539.
  31. Sunnetcioglu A, Arisoy A, Demir Y, Ekin S, Dogan E. Associations between the standardized uptake value of (18)F-FDG PET/CT and demographic, clinical, pathological, radiological factors in lung cancer. Int J Clin Exp Med 2015;8:15794-15800.
  32. Hsu HH, Ko KH, Chou YC, Lin LF, Tsai WC, Lee SC, et al. SUVmax and tumor size predict surgical outcome of synchronous multiple primary lung cancers. Medicine (Baltimore) 2016;95:e2351.
  33. Lopci E, Toschi L, Grizzi F, Rahal D, Olivari L, Castino GF, et al. Correlation of metabolic information on FDG-PET with tissue expression of immune markers in patients with non-small cell lung cancer (NSCLC) who are candidates for upfront surgery. Eur J Nucl Med Mol Imaging 2016;43:1954-1961.
  34. Vander Heiden MG, Cantley LC, Thompson CB. Understanding the Warburg effect: the metabolic requirements of cell proliferation. Science 2009;324:1029-1033.
  35. Avril N. GLUT1 expression in tissue and (18)F-FDG uptake. J Nucl Med 2004;45:930-932.
  36. Labiano S, Palazon A, Melero I. Immune response regulation in the tumor microenvironment by hypoxia. Semin Oncol 2015;42:378-386.
  37. Renner K, Singer K, Koehl GE, Geissler EK, Peter K, Siska PJ, et al. Metabolic hallmarks of tumor and immune cells in the tumor microenvironment. Front Immunol 2017;8:248.
  38. Sinicrope FA, Rego RL, Garrity-Park MM, Foster NR, Sargent DJ, Goldberg RM, et al. Alterations in cell proliferation and apoptosis in colon cancers with microsatellite instability. Int J Cancer 2007;120:1232-1238.
  39. Sukumar M, Roychoudhuri R, Restifo NP. Nutrient competition: a new axis of tumor immunosuppression. Cell 2015;162:1206-1208.
  40. Li XF, Du Y, Ma Y, Postel GC, Civelek AC. (18)F-fluorodeoxyglucose uptake and tumor hypoxia: revisit (18)f-fluorodeoxyglucose in oncology application. Transl Oncol 2014;7:240-247.
  41. Jeong YJ, Jung JW, Cho YY, Park SH, Oh HK, Kang S. Correlation of hypoxia inducible transcription factor in breast cancer and SUVmax of F-18 FDG PET/CT. Nucl Med Rev Cent East Eur 2017;20:32-38.
  42. Duechler M, Peczek L, Szubert M, Suzin J. Influence of hypoxia inducible factors on the immune microenvironment in ovarian cancer. Anticancer Res 2014;34:2811-2819.
  43. Facciabene A, Peng X, Hagemann IS, Balint K, Barchetti A, Wang LP, et al. Tumour hypoxia promotes tolerance and angiogenesis via CCL28 and T(reg) cells. Nature 2011;475:226-230.