Tumor Therapy Response: Preclinical & Clinical

Thursday 15 May 2014

Marie-France Penet¹, Delia Mezzanzanica², Franca Podo³, Max de Reggi⁴, Bouchra Gharib⁴, and Zaver M. Bhujwalla^1
1JHU ICMIC Program, Division of Cancer Imaging Research, The Johns Hopkins University School of Medicine, Baltimore, MD, United States, ²Unit of Molecular Therapies, Department of Experimental Oncology and Molecular Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy,³Department of Cell Biology and Neurosciences, Section of Molecular and Cellular Imaging, Istituto Superiore di Sanità, Rome, Italy, ⁴Neurobiology of Cellular Interactions and Neuropathophysiology, UMR CNRS 7259, Aix-Marseille University, Marseille, France

Epithelial ovarian cancer remains the leading cause of death from gynecologic malignancy among women in developed countries. New therapeutic strategies evaluated with relevant preclinical models are urgently needed to improve survival rates. Here we have assessed the effect of pantethine on tumor growth and metabolism using MRI and high resolution MRS, respectively, in an orthotopic model of ovarian cancer. We also investigated effects on metastases and ascites formation. Pantethine treatment resulted in slower tumor progression, decreased levels of phosphocholine and phosphatidylcholine, and reduced metastases and ascites occurrence.

Simon P Robinson¹, Naveen S Vasudev², and Andrew R Reynolds^2
1Division of Radiotherapy & Imaging, The Institute of Cancer Research, Sutton, Surrey, United Kingdom, ²Breakthrough Breast Cancer Research Centre, The Institute of Cancer Research, London, United Kingdom

The response of 786-O RCC xenografts to sunitinib was investigated using susceptibility contrast MRI with USPIO particles. Fractional blood volume (fBV) was significantly reduced after 2 weeks daily treatment in the absence of any change in tumour volume. This reduced fBV was maintained in 786-O xenografts exhibiting acquired resistance to sunitinib.

Miguel R. Goncalves¹, Simon Walker-Samuel¹, Rajiv Ramasawmy^1,2, Sean P. Johnson², R. Barbara Pedley², and Mark F. Lythgoe^1
1UCL Centre for Advanced Biomedical Imaging, Division of Medicine, London, United Kingdom, ²UCL Cancer Institute, London, United Kingdom

We present the results of a tumour therapy study with the antiangiogenic agent imatinib mesylate, which was assessed using gradient-echo MRI alongside hyperoxia and hypercapnia challenges. Median carbogen-ΔR2*, carbogen-ΔR1 and hypercapnia-ΔGRE-SI did not change with therapy. However, significant changes in the spatial heterogeneity of carbogen-ΔR2* and hypercapnia-ΔSI were observed. These results are possibly due to the combined effect of a number of localised phenomena, given the heterogeneous nature of the tumour vasculature.

Jin Li¹, Yann Jamin¹, Jessica K.R. Boult¹, John C. Waterton², Ralph Sinkus³, Michelle D. Garrett⁴, and Simon P. Robinson^1
1Division of Radiotherapy & Imaging, The Institute of Cancer Research, Sutton, Surrey, United Kingdom, ²Personalised Healthcare and Biomarkers, AstraZeneca, Macclesfield, Cheshire, United Kingdom, ³BHF Centre of Excellence, Division of Imaging Sciences and Biomedical Engineering, King's College London, King's Health Partners, St Thomas' Hospital, London, United Kingdom, ⁴Division of Cancer Therapeutics, The Institute of Cancer Research, Sutton, Surrey, United Kingdom

Comparison of MRE-derived imaging biomarkers of viscoelasticity (|G*|) and ADC in orthotopically propagated BT474 breast cancer xenografts revealed a close spatial association and quantitative correlation of reduced |G*| and elevated ADC with pathologically-confirmed cell death. A stronger and more significant correlation between |G*| and cell death supports |G*| as a potentially more sensitive biomarker of cell death than ADC.

Amanda M Hamilton¹, Sallouha Aidoudi-Ahmed², Venkata R Kotamraju², Shweta Sharma², Paula J Foster¹, Kazuki N Sugahara², Erkki Ruoslahti², and Brian K Rutt^3
1Robarts Research Institute, London, Ontario, Canada, ²Sanford-Burnham Medical Research Institute, California, United States, ³Stanford University, California, United States

MRI was used to evaluate the treatment efficacy of iRGD-NW, a magnetic nanoparticle coated with a tumor-penetrating peptide in a preclinical breast cancer brain metastasis model. Mice received saline, iRGD-NW (tumor-homing) or CRGDC-NW at day (td) 6 or 12 post-cell injection. Tumor formation was evaluated by MRI at two time points after treatment administration. Td6 iRGD-NW mice displayed significantly lower tumor burden and signal void retention than that of saline mice. There was no observed treatment effect for td12 mice. Results showed that iRGD-NW had a significant time-dependent effect on tumor burden and suggest a potential use in metastasis prevention.

Hyunki Kim¹, Desiree Morgan¹, David Sarver², Kyle Lee¹, T. Beasley¹, and James Posey^1
1University of Alabama at Birmingham, Birmingham, AL, United States, ²University of Arkansas for Medical Sciences, AR, United States

Quantitative DCE-MRI and DWI were successfully utilized in GIST patients to measure the perfusion and diffusion parameters of tumors. Significant decreases of Ktrans and kep values were observed in GISTs after sunitinib therapy, while tumor ADC values were significantly increased likely reflecting favorable anti-tumor effects. Tumor Ktrans change was significantly correlated with tumor-volume change, and therefore it may serve as an effective surrogate biomarker, especially when applied at earlier time points, to assess the therapeutic efficacy of sunitinib.

Wei Huang¹, Aneela Afzal¹, Megan L Holtorf¹, and Christopher W Ryan^1
1Oregon Health & Science University, Portland, Oregon, United States

DCE-MRI studies were performed on eight soft-tissue sarcoma patients to assess responses to treatment regimen of antiangiogenic agent plus conventinal chemoradiotherapy. Significant Ktrans and kep decreases were found in normal muscle regions adjacent to the tumor following initial 2 weeks of antiangiogenic therapy only. The results suggest that caution must be taken in DCE-MRI evaluation of response to antiangiogenic treatment using the reference tissue method.

Elizabeth AM O'Flynn¹, David Collins², James D'Arcy², Maria Schmidt², Kabir Mohammed³, and Nandita M deSouza^1
1Clinical Magnetic Resonance, Institute of Cancer Research and Royal Marsden Hospital, Sutton, Surrey, United Kingdom, ²Clinical Magnetic Resonance, Insitute of Cancer Research, Sutton, Surrey, United Kingdom, ³Statistics, Royal Marsden Hospital, Sutton, Surrey, United Kingdom

We investigate the role of multiparametric MRI in the prediction of response to neoadjuvant chemotherapy (NAC) in breast cancer. 27 women underwent breast MRI at 3T prior to and after two cycles of NAC. Values for ADC, R2*, Ktrans, ve, kep and IAUGC were recorded pixel-by-pixel. The enhancement fraction (EF) was calculated for each patient. The percentage decrease in EF after 2 cycles was the best predictor of complete pathological response on discriminant analysis. EF should be considered as a potential biomarker for predicting response to NAC.

Alina Tudorica¹, Karen Y Oh¹, Stephen Y-C Chui¹, Nicole Roy¹, Megan L Troxell¹, Yiyi Chen¹, Arpana Naik¹, Megan L Holtorf¹, Aneela Afzal¹, Zunqiu Chen¹, Charles S Springer¹, Xin Li¹, and Wei Huang^1
1Oregon Health & Science University, Portland, Oregon, United States

Fifteen women with breast cancer underwent DCE-MRI before, during, and after neoadjuvant chemotherapy. Pharmacokinetic analysis of DCE-MRI data were performed using Standard (Tofts) model (SM) and Shutter-Speed model (SSM). After only one cycle of therapy, % changes in SM and SSM Ktrans and kep, and SSM-unique Tau_i, as well as absolute values of Ktrans and kep, provieded excellent early predictions of pathologic complete response. Following therapy completion, tumor Tau_i was inversely, while Ktrans and tumor size were positively, correlated with residual disease burden. In conclusion, DCE-MRI functional parameters provided earlier prediction of response and more accurate assessment of residual disease compared to tumor size measurement.

Wei Huang¹, Xin Li¹, Xia Li², Ming-Ching Chang³, Matthew J Oborski⁴, Dariya I Malyarenko⁵, Mark Muzi⁶, Guido H Jajamovich⁷, Andriy Fedorov⁸, Yiyi Chen¹, Alina Tudorica¹, Sandeep N Gupta³, Charles M Laymon⁴, Kenneth I Marro⁶, Hadrien A Dyvorne⁷, James V Miller³, Thomas L Chenevert⁵, Thomas E Yankeelov², James M Mountz⁴, Paul E Kinahan⁶, Ron Kikinis⁸, Bachir Taouli⁷, Fiona Fennessy⁸, and Jayashree Kalpathy-Cramer^9
1Oregon Health & Science University, Portland, Oregon, United States, ²Vanderbilt University, Nashville, Tennessee, United States, ³General Electric Global Research, Niskayuna, New York, United States, ⁴University of Pittsburgh, Pittsburgh, Pennsylvania, United States, ⁵University of Michigan, Ann Arbor, Michigan, United States, ⁶University of Washington, Seattle, Washington, United States, ⁷Icahn School of Medicine at Mount Sinai, New York, New York, United States, ⁸Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, United States, ⁹Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States

Seven institutions of the NCI-sponsored Quantitative Imaging Network (QIN) participated in a DCE-MRI data analysis challenge, in which 12 pharmacokinetic models/algorithms (including Tofts model, extended Tofts model, and Shutter-Speed model) were used to analyze shared breast DCE-MRI data collected at one center before and after one cycle of neoadjuvant chemotherapy, from 10 breast cancer patients. Tumor ROI definition, AIF, and precontrast T1 were fixed for analysis of each data set across all algorithms. Considerable variations in DCE-MRI parameters were found among the algoritms with Ktrans wCV as high as 0.59. Encouragingly, Ktrans and kep values after one therapy cyles and their % changes (relative to baselin) obtained from all algorithms provided good to excellent early prediction of pathologic response.