Volume-based predictive biomarkers of sequential FDG-PET/CT for sunitinib in cancer of unknown primary: identification of the best benefited patients

  • Yifei Ma
  • Wei Xu
  • Ruojing Bai
  • Yiming Li
  • Hongyu YuEmail author
  • Chunshan Yang
  • Huazheng Shi
  • Jian Zhang
  • Jidong Li
  • Chenguang Wang
  • Jianru XiaoEmail author
Original Article



To test the performance of sequential 18F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) in predicting survival after sunitinib therapies in patients with cancer of unknown primary (CUP).


CUP patients were enrolled for sequential PET/CT scanning for sunitinib and a control group. Univariate and multivariate analysis were applied to test the efficacy of sunitinib therapy in CUP patients. Next, sequential analyses involving PET/CT parameters were performed to identify and validate sensitive PET/CT biomarkers for sunitinib therapy. Finally, time-dependent receiver operating characteristic (TDROC) analyses were performed to compare the predictive accuracy.


Multivariate analysis proved that sunitinib group had significantly improved survival (p < 0.01) as compared to control group. After cycle 2 of therapy, multivariate analysis identified volume-based PET/CT parameters as sensitive biomarkers for sunitinib (p < 0.01). TDROC curves demonstrated whole-body total lesion glycolysis reduction (Δ WTLG) and follow-up WTLG to have good accuracy for efficacy prediction. This evidence was validated after cycle 4 of therapy with the same method.


Sunitinib therapy proved effective in treatment of CUP. PET/CT volume-based parameters may help predict outcome of sunitinib therapy, in which Δ WTLG and follow-up WTLG seem to be sensitive biomarkers for sunitinib efficacy. Patients with greater reduction and lower WTLG at follow-up seem to have better survival outcome.


Volume-based PET/CT parameters Survival prediction Sunitinib Cancer of unknown primary 


Compliance with ethical standards


This study was supported by the joint taking program of key disease (Grant 2014ZYJB0103) and the Shanghai Youth Science and Technology Talent Sailing Program (Grant 14YF1405900).

Conflicts of interest


Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional review board and with the principles of the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards.

Informed consent

All patients gave informed consent to the treatment, PET/CT scanning and participation in study.

Supplementary material

259_2016_3504_MOESM1_ESM.docx (67 kb)
ESM 1 (DOCX 67.4 kb)


  1. 1.
    Varadhachary GR, Raber MN. Cancer of unknown primary site. N Engl J Med. 2014;371(8):757–65.CrossRefGoogle Scholar
  2. 2.
    Briasoulis E, Tolis C, Bergh J, Pavlidis N. ESMO minimum clinical recommendations for diagnosis, treatment and follow-up of cancers of unknown primary site (CUP). Ann Oncol. 2005;16 Suppl 1:i75–6.CrossRefGoogle Scholar
  3. 3.
    Pavlidis N, Pentheroudakis G. Cancer of unknown primary site. Lancet. 2012;379:1428–35.CrossRefGoogle Scholar
  4. 4.
    Golfinopoulos V, Pentheroudakis G, Salanti G, Nearchou AD, Ioannidis JP, Pavlidis N. Comparative survival with diverse chemotherapy regimens for cancer of unknown primary site: multiple-treatments meta-analysis. Cancer Treat Rev. 2009;35:570–3.CrossRefGoogle Scholar
  5. 5.
    Greco FA, Pavlidis N. Treatment for patients with unknown primary carcinoma and unfavorable prognostic factors. Semin Oncol. 2009;36:65–74.CrossRefGoogle Scholar
  6. 6.
    Greco FA, Hainsworth JD. Cancer of unknown primary site. In: DeVita Jr VT, Hellman S, Rosenberg SA, editors. Cancer: principles and practice of oncology. 8th ed. Philadelphia: Lippincott Williams & Wilkins; 2008. p. 2363–87.Google Scholar
  7. 7.
    Motzer RJ, Rini BI, Bukowski RM, et al. Sunitinib in patients with metastatic renal cell carcinoma. JAMA. 2006;295:2516–24.CrossRefGoogle Scholar
  8. 8.
    George S, Blay JY, Casali PG, et al. Clinical evaluation of continuous daily dosing of sunitinib malate in patients with advanced gastrointestinal stromal tumour after imatinib failure. Eur J Cancer. 2009;45:1959–68.CrossRefGoogle Scholar
  9. 9.
    Castellano D et al. Therapy management with sunitinib in patients with metastatic renal cell carcinoma: key concepts and the impact of clinical biomarkers. Cancer Treat Rev. 2013;39:230–40.CrossRefGoogle Scholar
  10. 10.
    Imbulgoda A et al. Sunitinib in the treatment of advanced solid tumors. Small Mol Oncol. 2014;13:165–78.CrossRefGoogle Scholar
  11. 11.
    Thézé B, Bernards N, et al. Monitoring therapeutic efficacy of sunitinib using [18F]FDG and [18F]FMISO PET in an immunocompetent model of luminal B (HER2-positive)-type mammary carcinoma. BMC Cancer. 2015;15:534–8.CrossRefGoogle Scholar
  12. 12.
    Kayani I, Avril N, Bomanji J, Chowdhury S, Rockall A, Sahdev A, et al. Sequential FDG-PET/CT as a biomarker of response to sunitinib in metastatic clear cell renal cancer. Clin Cancer Res. 2011;17(18):6021–8.CrossRefGoogle Scholar
  13. 13.
    Vesselle H, Freeman JD, Wiens L, et al. Fluorodeoxyglucose uptake of primary non–small cell lung cancer at positron emission tomography: new contrary data on prognostic role. Clin Cancer Res. 2007;13(11):3255–63.CrossRefGoogle Scholar
  14. 14.
    Chung MK, Jeong HS, Park SG, et al. Metabolic tumor volume of [18F]- fluorodeoxyglucose positron emission tomography/computed tomography predicts short-term outcome to radiotherapy with or without chemotherapy in pharyngeal cancer. Clin Cancer Res. 2009;15:5861–8.CrossRefGoogle Scholar
  15. 15.
    Vesselle H, Schmidt RA, Pugsley JM, et al. Lung cancer proliferation correlates with [F-18] fluorodeoxyglucose uptake by positron emission tomography. Clin Cancer Res. 2000;6(10):3837–44.PubMedPubMedCentralGoogle Scholar
  16. 16.
    Tang Y et al. Effect of surgery on quality of life of patients with spinal metastasis from non-small-cell lung cancer. J Bone Joint Surg Am. 2016;98:396–402.CrossRefGoogle Scholar
  17. 17.
    Pfizer Inc. SUTENT, Summary of product characteristics. July 2010.
  18. 18.
    Maita S, Yuasa T, et al. Antitumor effect of sunitinib against skeletal metastatic renal cell carcinoma through inhibition of osteoclast function. Int J Cancer. 2012;130:677–84.CrossRefGoogle Scholar
  19. 19.
    Satoh Y, Onishi H, Nambu A, Araki T. Volume-based parameters measured by using FDG PET/CT in patients with stage I NSCLC treated with stereotactic body radiation therapy: prognostic value. Radiology. 2014;270(1):275–81.CrossRefGoogle Scholar
  20. 20.
    Satoh et al. Whole-body total lesion glycolysis measured on fluorodeoxyglucose positron emission tomography/computed tomography as a prognostic variable in metastatic breast cancer. BMC Cancer. 2014,14:525.Google Scholar
  21. 21.
    Kaplan EL, Meier P. Non parametric estimation from incomplete observations. J Am Stat Assoc. 1958;53:457–81.CrossRefGoogle Scholar
  22. 22.
    Hyun SH, Choi JY, Kim K, Kim J, Shim YM, Um SW, et al. Volume-based parameters of 18F-fluorodeoxyglucose positron emission tomography/computed tomography improve outcome prediction in early-stage non–small cell lung cancer after surgical resection. Ann Surg. 2013;257(2):364–70.CrossRefGoogle Scholar
  23. 23.
    Cox DR. Regression models and life tables. J R Stat Soc. 1972;34:187–220.Google Scholar
  24. 24.
    Heagerty PJ, Lumley T, Pepe MS. Time-dependent ROC curves for censored survival data and a diagnostic marker. Biometrics. 2000;56:337–44.CrossRefGoogle Scholar
  25. 25.
    Ma Y, Zhou W, He S, Xu W, Xiao J. Tyrosine kinase inhibitor sunitinib therapy is effective in the treatment of bone metastasis from cancer of unknown primary: identification of clinical and immunohistochemical biomarkers predicting survival. Int J Cancer. 2016;139(6):1423–30.CrossRefGoogle Scholar
  26. 26.
    Ma Y, Xu W, Liang Z, Li Y, Yu H, Yang C, Li J, Xiao J. Patient-oncologist Alliance and Psychosocial Well-being in Chinese Society Strongly Affect Cancer Management Adherence with Cancer of Unknown Primary. Psycho-oncology. 2016. doi: 10.1002/pon.4245.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Yifei Ma
    • 1
    • 2
  • Wei Xu
    • 1
  • Ruojing Bai
    • 3
  • Yiming Li
    • 4
  • Hongyu Yu
    • 2
    Email author
  • Chunshan Yang
    • 5
    • 6
  • Huazheng Shi
    • 6
  • Jian Zhang
    • 6
  • Jidong Li
    • 7
  • Chenguang Wang
    • 8
  • Jianru Xiao
    • 1
    Email author
  1. 1.Department of Orthorpedic Oncology, Changzheng HospitalSecond Military Medical UniversityShanghaiChina
  2. 2.Department of Pathology, Changzheng HospitalSecond Military Medical UniversityShanghaiChina
  3. 3.Department of Geriatrics, Tianjin Medical University General Hospital, Laboratory of Neuro-Trauma and Neurodegenerative DisorderGeriatrics InstituteTianjinChina
  4. 4.Department of Neuro-oncologyNeurosurgery InstituteBeijingChina
  5. 5.Department of PET/CT RadiologyPanorama Medical Imaging CenterShanghaiChina
  6. 6.Department of PET/CT Radiology CenterShanghaiChina
  7. 7.Department of StomatologyThe First People’s Hospital of ShangqiuShangqiuChina
  8. 8.Department of Radiology, Changzheng HospitalSecond Military Medical UniversityShanghaiChina

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