Top

European Journal of Nuclear Medicine and Molecular Imaging

Published in:

Open Access 08-09-2022 | Magnetic Resonance Imaging | Original Article

Functional biomarkers derived from computed tomography and magnetic resonance imaging differentiate PDAC subgroups and reveal gemcitabine-induced hypo-vascularization

Authors: Irina Heid, Marija Trajkovic-Arsic, Fabian Lohöfer, Georgios Kaissis, Felix N. Harder, Moritz Mayer, Geoffrey J. Topping, Friderike Jungmann, Barbara Crone, Moritz Wildgruber, Uwe Karst, Lucia Liotta, Hana Algül, Hsi-Yu Yen, Katja Steiger, Wilko Weichert, Jens T. Siveke, Marcus R. Makowski, Rickmer F. Braren

Published in: European Journal of Nuclear Medicine and Molecular Imaging | Issue 1/2022

Abstract

Purpose

Pancreatic ductal adenocarcinoma (PDAC) is a molecularly heterogeneous tumor entity with no clinically established imaging biomarkers. We hypothesize that tumor morphology and physiology, including vascularity and perfusion, show variations that can be detected by differences in contrast agent (CA) accumulation measured non-invasively. This work seeks to establish imaging biomarkers for tumor stratification and therapy response monitoring in PDAC, based on this hypothesis.

Methods and materials

Regional CA accumulation in PDAC was correlated with tumor vascularization, stroma content, and tumor cellularity in murine and human subjects. Changes in CA distribution in response to gemcitabine (GEM) were monitored longitudinally with computed tomography (CT) Hounsfield Units ratio (HUr) of tumor to the aorta or with magnetic resonance imaging (MRI) ΔR₁ area under the curve at 60 s tumor-to-muscle ratio (AUC60r). Tissue analyses were performed on co-registered samples, including endothelial cell proliferation and cisplatin tissue deposition as a surrogate of chemotherapy delivery.

Results

Tumor cell poor, stroma-rich regions exhibited high CA accumulation both in human (meanHUr 0.64 vs. 0.34, p < 0.001) and mouse PDAC (meanAUC60r 2.0 vs. 1.1, p < 0.001). Compared to the baseline, in vivo CA accumulation decreased specifically in response to GEM treatment in a subset of human (HUr −18%) and mouse (AUC60r −36%) tumors. Ex vivo analyses of mPDAC showed reduced cisplatin delivery (GEM: 0.92 ± 0.5 mg/g, vs. vehicle: 3.1 ± 1.5 mg/g, p = 0.004) and diminished endothelial cell proliferation (GEM: 22.3% vs. vehicle: 30.9%, p = 0.002) upon GEM administration.

Conclusion

In PDAC, CA accumulation, which is related to tumor vascularization and perfusion, inversely correlates with tumor cellularity. The standard of care GEM treatment results in decreased CA accumulation, which impedes drug delivery. Further investigation is warranted into potentially detrimental effects of GEM in combinatorial therapy regimens.

Available only for authorised users

Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021; https://doi.org/10.3322/caac.21660.

Society AC. Cancer Facts and Figures 2014-2021.

Neoptolemos JP, Kleeff J, Michl P, Costello E, Greenhalf W, Palmer DH. Therapeutic developments in pancreatic cancer: current and future perspectives. Nat Rev Gastroenterol Hepatol. 2018;15:333–48. https://doi.org/10.1038/s41575-018-0005-x.CrossRefPubMed

Provenzano PP, Cuevas C, Chang AE, Goel VK, Von Hoff DD, Hingorani SR. Enzymatic targeting of the stroma ablates physical barriers to treatment of pancreatic ductal adenocarcinoma. Cancer Cell. 2012;21:418–29. https://doi.org/10.1016/j.ccr.2012.01.007.CrossRefPubMedPubMedCentral

Jacobetz MA, Chan DS, Neesse A, Bapiro TE, Cook N, Frese KK, et al. Hyaluronan impairs vascular function and drug delivery in a mouse model of pancreatic cancer. Gut. 2013;62:112–20. https://doi.org/10.1136/gutjnl-2012-302529.CrossRefPubMed

Hosein AN, Brekken RA, Maitra A. Pancreatic cancer stroma: an update on therapeutic targeting strategies. Nat Rev Gastroenterol Hepatol. 2020;17:487–505. https://doi.org/10.1038/s41575-020-0300-1.CrossRefPubMedPubMedCentral

Garcia-Sampedro A, Gaggia G, Ney A, Mahamed I, Acedo P. The state-of-the-art of phase II/III clinical trials for targeted pancreatic cancer therapies. J Clin Med. 2021;10 https://doi.org/10.3390/jcm10040566.

Burris HA 3rd, Moore MJ, Andersen J, Green MR, Rothenberg ML, Modiano MR, et al. Improvements in survival and clinical benefit with gemcitabine as first-line therapy for patients with advanced pancreas cancer: a randomized trial. J Clin Oncol. 1997;15:2403–13. https://doi.org/10.1200/JCO.1997.15.6.2403.CrossRefPubMed

Ramanathan RK, McDonough SL, Philip PA, Hingorani SR, Lacy J, Kortmansky JS, et al. Phase IB/II Randomized Study of FOLFIRINOX Plus Pegylated Recombinant Human Hyaluronidase Versus FOLFIRINOX Alone in Patients With Metastatic Pancreatic Adenocarcinoma: SWOG S1313. J Clin Oncol. 2019;37:1062–9. https://doi.org/10.1200/JCO.18.01295.CrossRefPubMedPubMedCentral

10.

Catenacci DV, Junttila MR, Karrison T, Bahary N, Horiba MN, Nattam SR, et al. Randomized phase Ib/II study of gemcitabine plus placebo or vismodegib, a hedgehog pathway inhibitor, in patients with metastatic pancreatic cancer. J Clin Oncol. 2015;33:4284–92. https://doi.org/10.1200/JCO.2015.62.8719.CrossRefPubMedPubMedCentral

11.

Van Cutsem E, Tempero MA, Sigal D, Oh DY, Fazio N, Macarulla T, et al. Randomized phase III trial of pegvorhyaluronidase alfa with nab-paclitaxel plus gemcitabine for patients with hyaluronan-high metastatic pancreatic adenocarcinoma. J Clin Oncol. 2020;38:3185–94. https://doi.org/10.1200/JCO.20.00590.CrossRefPubMedPubMedCentral

12.

Conroy T, Desseigne F, Ychou M, Bouche O, Guimbaud R, Becouarn Y, et al. FOLFIRINOX versus gemcitabine for metastatic pancreatic cancer. N Engl J Med. 2011;364:1817–25. https://doi.org/10.1056/NEJMoa1011923.CrossRefPubMed

13.

Von Hoff DD, Ervin T, Arena FP, Chiorean EG, Infante J, Moore M, et al. Increased survival in pancreatic cancer with nab-paclitaxel plus gemcitabine. N Engl J Med. 2013;369:1691–703. https://doi.org/10.1056/NEJMoa1304369.CrossRef

14.

Koay EJ, Truty MJ, Cristini V, Thomas RM, Chen R, Chatterjee D, et al. Transport properties of pancreatic cancer describe gemcitabine delivery and response. J Clin Invest. 2014;124:1525–36. https://doi.org/10.1172/JCI73455.CrossRefPubMedPubMedCentral

15.

Buchholz SM, Goetze RG, Singh SK, Ammer-Herrmenau C, Richards FM, Jodrell DI, et al. Depletion of macrophages improves therapeutic response to gemcitabine in murine pancreas cancer. Cancers (Basel). 2020;12 https://doi.org/10.3390/cancers12071978.

16.

Hessmann E, Patzak MS, Klein L, Chen N, Kari V, Ramu I, et al. Fibroblast drug scavenging increases intratumoural gemcitabine accumulation in murine pancreas cancer. Gut. 2018;67:497–507. https://doi.org/10.1136/gutjnl-2016-311954.CrossRefPubMed

17.

Laquente B, Lacasa C, Ginesta MM, Casanovas O, Figueras A, Galan M, et al. Antiangiogenic effect of gemcitabine following metronomic administration in a pancreas cancer model. Mol Cancer Ther. 2008;7:638–47. https://doi.org/10.1158/1535-7163.MCT-07-2122.CrossRefPubMed

18.

Cao J, Pickup S, Clendenin C, Blouw B, Choi H, Kang D, et al. Dynamic contrast-enhanced MRI detects responses to stroma-directed therapy in mouse models of pancreatic Ductal Adenocarcinoma. Clin Cancer Res. 2019;25:2314–22. https://doi.org/10.1158/1078-0432.CCR-18-2276.CrossRefPubMed

19.

Cham KK, Baker JH, Takhar KS, Flexman JA, Wong MQ, Owen DA, et al. Metronomic gemcitabine suppresses tumour growth, improves perfusion, and reduces hypoxia in human pancreatic ductal adenocarcinoma. Br J Cancer. 2010;103:52–60. https://doi.org/10.1038/sj.bjc.6605727.CrossRefPubMedPubMedCentral

20.

Yapp DT, Wong MQ, Kyle AH, Valdez SM, Tso J, Yung A, et al. The differential effects of metronomic gemcitabine and antiangiogenic treatment in patient-derived xenografts of pancreatic cancer: treatment effects on metabolism, vascular function, cell proliferation, and tumor growth. Angiogenesis. 2016;19:229–44. https://doi.org/10.1007/s10456-016-9503-z.CrossRefPubMedPubMedCentral

21.

Hamdy A, Ichikawa Y, Toyomasu Y, Nagata M, Nagasawa N, Nomoto Y, et al. Perfusion CT to assess response to neoadjuvant chemotherapy and radiation therapy in pancreatic ductal adenocarcinoma: initial experience. Radiology. 2019;292:628–35. https://doi.org/10.1148/radiol.2019182561.CrossRefPubMed

22.

Kannan P, Kretzschmar WW, Winter H, Warren D, Bates R, Allen PD, et al. Functional parameters derived from magnetic resonance imaging reflect vascular morphology in preclinical tumors and in human liver metastases. Clin Cancer Res. 2018;24:4694–704. https://doi.org/10.1158/1078-0432.CCR-18-0033.CrossRefPubMedPubMedCentral

23.

Rajendran R, Huang W, Tang AM, Liang JM, Choo S, Reese T, et al. Early detection of antiangiogenic treatment responses in a mouse xenograft tumor model using quantitative perfusion MRI. Cancer Med. 2014;3:47–60. https://doi.org/10.1002/cam4.177.CrossRefPubMedPubMedCentral

24.

Nebuloni L, Kuhn GA, Vogel J, Muller R. A novel in vivo vascular imaging approach for hierarchical quantification of vasculature using contrast enhanced micro-computed tomography. PLoS One. 2014;9:e86562. https://doi.org/10.1371/journal.pone.0086562.CrossRefPubMedPubMedCentral

25.

Torphy RJ, Wang Z, True-Yasaki A, Volmar KE, Rashid N, Yeh B, et al. Stromal content is correlated with tissue site, contrast retention, and survival in pancreatic adenocarcinoma. JCO Precis Oncol. 2018;2018 https://doi.org/10.1200/PO.17.00121.

26.

Koay EJ, Lee Y, Cristini V, Lowengrub JS, Kang Y, Lucas FAS, et al. A visually apparent and quantifiable CT imaging feature identifies biophysical subtypes of pancreatic ductal adenocarcinoma. Clin Cancer Res. 2018;24:5883–94. https://doi.org/10.1158/1078-0432.CCR-17-3668.CrossRefPubMedPubMedCentral

27.

Jungmann F, Kaissis GA, Ziegelmayer S, Harder F, Schilling C, Yen HY, et al. Prediction of tumor cellularity in resectable PDAC from preoperative computed tomography imaging. Cancers (Basel). 2021;13 https://doi.org/10.3390/cancers13092069.

28.

Tofts PS, Brix G, Buckley DL, Evelhoch JL, Henderson E, Knopp MV, et al. Estimating kinetic parameters from dynamic contrast-enhanced T(1)-weighted MRI of a diffusable tracer: standardized quantities and symbols. J Magn Reson Imaging. 1999;10:223–32. https://doi.org/10.1002/(SICI)1522-2586(199909)10:33.0.CO;2-S.CrossRefPubMed

29.

Tang W, Liu W, Li HM, Wang QF, Fu CX, Wang XH, et al. Quantitative dynamic contrast-enhanced MR imaging for the preliminary prediction of the response to gemcitabine-based chemotherapy in advanced pancreatic ductal carcinoma. Eur J Radiol. 2019;121:108734. https://doi.org/10.1016/j.ejrad.2019.108734.CrossRefPubMed

30.

Pijnappel EN, Wassenaar NPM, Gurney-Champion OJ, Klaassen R, van der Lee K, Pleunis-van Empel MCH, et al. Phase I/II study of LDE225 in combination with gemcitabine and nab-paclitaxel in patients with metastatic pancreatic cancer. Cancers (Basel). 2021;13 https://doi.org/10.3390/cancers13194869.

31.

Kinh Do R, Reyngold M, Paudyal R, Oh JH, Konar AS, LoCastro E, et al. Diffusion-weighted and dynamic contrast-enhanced MRI derived imaging metrics for stereotactic body radiotherapy of pancreatic ductal adenocarcinoma: preliminary findings. Tomography. 2020;6:261–71. https://doi.org/10.18383/j.tom.2020.00015.CrossRefPubMedPubMedCentral

32.

Klaassen R, Steins A, Gurney-Champion OJ, Bijlsma MF, van Tienhoven G, Engelbrecht MRW, et al. Pathological validation and prognostic potential of quantitative MRI in the characterization of pancreas cancer: preliminary experience. Mol Oncol. 2020;14:2176–89. https://doi.org/10.1002/1878-0261.12688.CrossRefPubMedPubMedCentral

33.

Khalifa F, Soliman A, El-Baz A, Abou El-Ghar M, El-Diasty T, Gimel'farb G, et al. Models and methods for analyzing DCE-MRI: a review. Med Phys. 2014;41:124301. https://doi.org/10.1118/1.4898202.CrossRefPubMed

34.

Chen CFHL, Lui CC, Lee CC, Weng HH, Tsai YH, Liu HL. In vivo correlation between semi-quantitative hemodynamic parameters and ktrans derived from DCE-MRI of brain tumors. Inc Int J Imaging Syst Technol. 2012;22:132–6. https://doi.org/10.1002/ima.22013.CrossRef

35.

Steingoetter A, Svensson J, Kosanke Y, Botnar RM, Schwaiger M, Rummeny E, et al. Reference region-based pharmacokinetic modeling in quantitative dynamic contract-enhanced MRI allows robust treatment monitoring in a rat liver tumor model despite cardiovascular changes. Magn Reson Med. 2011;65:229–38. https://doi.org/10.1002/mrm.22589.CrossRefPubMed

36.

Mendler CT, Feuchtinger A, Heid I, Aichler M, D'Alessandria C, Pirsig S, et al. Tumor uptake of anti-CD20 Fabs depends on tumor perfusion. J Nucl Med. 2016;57:1971–7. https://doi.org/10.2967/jnumed.116.176784.CrossRefPubMed

37.

Heid I, Steiger K, Trajkovic-Arsic M, Settles M, Esswein MR, Erkan M, et al. Co-clinical assessment of tumor cellularity in pancreatic cancer. Clin Cancer Res. 2017;23:1461–70. https://doi.org/10.1158/1078-0432.Ccr-15-2432.CrossRefPubMed

38.

Trajkovic-Arsic M, Heid I, Steiger K, Gupta A, Fingerle A, Worner C, et al. Apparent Diffusion Coefficient (ADC) predicts therapy response in pancreatic ductal adenocarcinoma. Sci Rep. 2017;7:17038. https://doi.org/10.1038/s41598-017-16826-z.CrossRefPubMedPubMedCentral

39.

Braren R, Curcic J, Remmele S, Altomonte J, Ebert O, Rummeny EJ, et al. Free-breathing quantitative dynamic contrast-enhanced magnetic resonance imaging in a rat liver tumor model using dynamic radial T(1) mapping. Invest Radiol. 2011;46:624–31. https://doi.org/10.1097/RLI.0b013e31821e30e7.CrossRefPubMed

40.

Ballke S, Heid I, Mogler C, Braren R, Schwaiger M, Weichert W, et al. Correlation of in vivo imaging to morphomolecular pathology in translational research: challenge accepted. EJNMMI Res. 2021;11:83. https://doi.org/10.1186/s13550-021-00826-2.CrossRefPubMedPubMedCentral

41.

Winter JM, Ting AH, Vilardell F, Gallmeier E, Baylin SB, Hruban RH, et al. Absence of E-cadherin expression distinguishes noncohesive from cohesive pancreatic cancer. Clin Cancer Res. 2008;14:412–8. https://doi.org/10.1158/1078-0432.CCR-07-0487.CrossRefPubMed

42.

Olive KP, Jacobetz MA, Davidson CJ, Gopinathan A, McIntyre D, Honess D, et al. Inhibition of Hedgehog signaling enhances delivery of chemotherapy in a mouse model of pancreatic cancer. Science. 2009;324:1457–61. https://doi.org/10.1126/science.1171362.CrossRefPubMedPubMedCentral

43.

Matuszewska K, Pereira M, Petrik D, Lawler J, Petrik J. Normalizing tumor vasculature to reduce hypoxia, enhance perfusion, and optimize therapy uptake. Cancers (Basel). 2021;13 https://doi.org/10.3390/cancers13174444.

44.

Ko AH, LoConte N, Tempero MA, Walker EJ, Kate Kelley R, Lewis S, et al. A phase I study of FOLFIRINOX plus IPI-926, a hedgehog pathway inhibitor, for advanced pancreatic adenocarcinoma. Pancreas. 2016;45:370–5. https://doi.org/10.1097/MPA.0000000000000458.CrossRefPubMedPubMedCentral

45.

Mpekris F, Baish JW, Stylianopoulos T, Jain RK. Role of vascular normalization in benefit from metronomic chemotherapy. Proc Natl Acad Sci USA. 2017;114:1994–9. https://doi.org/10.1073/pnas.1700340114.CrossRefPubMedPubMedCentral

46.

Kersemans V, Kannan P, Beech JS, Bates R, Irving B, Gilchrist S, et al. Improving in vivo high-resolution CT imaging of the tumour vasculature in xenograft mouse models through reduction of motion and bone-streak artefacts. PLoS ONE. 2015;10:e0128537. https://doi.org/10.1371/journal.pone.0128537.CrossRefPubMedPubMedCentral

Title: Functional biomarkers derived from computed tomography and magnetic resonance imaging differentiate PDAC subgroups and reveal gemcitabine-induced hypo-vascularization
Authors: Irina Heid
Marija Trajkovic-Arsic
Fabian Lohöfer
Georgios Kaissis
Felix N. Harder
Moritz Mayer
Geoffrey J. Topping
Friderike Jungmann
Barbara Crone
Moritz Wildgruber
Uwe Karst
Lucia Liotta
Hana Algül
Hsi-Yu Yen
Katja Steiger
Wilko Weichert
Jens T. Siveke
Marcus R. Makowski
Rickmer F. Braren
Publication date: 08-09-2022
Publisher: Springer Berlin Heidelberg
Keywords: Magnetic Resonance Imaging
Magnetic Resonance Imaging
Computed Tomography
Computed Tomography
Biomarkers
Published in: European Journal of Nuclear Medicine and Molecular Imaging / Issue 1/2022
Print ISSN: 1619-7070
Electronic ISSN: 1619-7089
DOI: https://doi.org/10.1007/s00259-022-05930-6

Keynote webinar | Spotlight on sleep in brain health

Springer Medicine

Functional biomarkers derived from computed tomography and magnetic resonance imaging differentiate PDAC subgroups and reveal gemcitabine-induced hypo-vascularization

Abstract

Purpose

Methods and materials

Results

Conclusion

Keynote webinar | Spotlight on sleep in brain health

Springer Medicine

Abstract

Purpose

Methods and materials

Results

Conclusion

Please log in to get access to this content

Other articles of this Issue 1/2022

[18F]FAPI-42 PET/CT versus [18F]FDG PET/CT for imaging of recurrent or metastatic gastrointestinal stromal tumors

Lymph node classification in E‑PSMA reporting guidelines for PSMA‑PET

CXCR4-targeted molecular imaging after severe SARS-Cov-2 infection

Theranostic application of 64Cu/177Lu-labeled anti-Trop2 monoclonal antibody in pancreatic cancer tumor models

Reducing instability of inter-subject covariance of FDG uptake networks using structure-weighted sparse estimation approach

Correction to: [18F]FAPI‑42 PET/CT versus [18F]FDG PET/CT for imaging of recurrent or metastatic gastrointestinal stromal tumors