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Multimodal Molecular Imaging of the Tumour Microenvironment

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Tumor Microenvironment

Part of the book series: Advances in Experimental Medicine and Biology ((AEMB,volume 1225))

Abstract

The tumour microenvironment (TME) surrounding tumour cells is a highly dynamic and heterogeneous composition of immune cells, fibroblasts, precursor cells, endothelial cells, signalling molecules and extracellular matrix (ECM) components. Due to the heterogeneity and the constant crosstalk between the TME and the tumour cells, the components of the TME are important prognostic parameters in cancer and determine the response to novel immunotherapies. To improve the characterization of the TME, novel non-invasive imaging paradigms targeting the complexity of the TME are urgently needed.

The characterization of the TME by molecular imaging will (1) support early diagnosis and disease follow-up, (2) guide (stereotactic) biopsy sampling, (3) highlight the dynamic changes during disease pathogenesis in a non-invasive manner, (4) help monitor existing therapies, (5) support the development of novel TME-targeting therapies and (6) aid stratification of patients, according to the cellular composition of their tumours in correlation to their therapy response.

This chapter will summarize the most recent developments and applications of molecular imaging paradigms beyond FDG for the characterization of the dynamic molecular and cellular changes in the TME.

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Change history

  • 05 January 2021

    Unfortunately the book was published with the incorrect citations in the appendix section of chapter 5. Now the citation has been updated.

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Acknowledgements

This work was partly supported by the EU seventh Framework Programme (FP7/2007–2013) under grant agreement n° 278850 (INMiND), the Horizon2020 Programme under grant agreement n° 675417 (PET3D), the “Cells-in-Motion” Cluster of Excellence (DFG EXC1003 – CiM) and the Interdisciplinary Center for Clinical Research (IZKF core unit PIX), Münster, Germany.

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Authors and Affiliations

  1. European Institute for Molecular Imaging (EIMI), University of Münster, Münster, Germany

    Claudia Foray, Cristina Barca, Philipp Backhaus, Sonja Schelhaas, Michael Schäfers, Andreas H. Jacobs & Bastian Zinnhardt

  2. PET Imaging in Drug Design and Development (PET3D), Münster, Germany

    Claudia Foray, Cristina Barca, Andreas H. Jacobs & Bastian Zinnhardt

  3. Department of Nuclear Medicine, University Hospital Münster, Westfälische Wilhelms University Münster, Münster, Germany

    Philipp Backhaus, Michael Schäfers & Bastian Zinnhardt

  4. UMR 1023, IMIV, Service Hospitalier Frédéric Joliot, CEA, Inserm, Université Paris Sud, CNRS, Université Paris-Saclay, Orsay, France

    Alexandra Winkeler

  5. Paris Centre de Recherche Cardiovasculaire, INSERM-U970, Université Paris Descartes, Paris, France

    Thomas Viel

  6. Department of Neurology, University Hospital Münster, Münster, Germany

    Oliver Grauer

  7. Department of Geriatrics, Johanniter Hospital, Evangelische Kliniken, Bonn, Germany

    Andreas H. Jacobs

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  1. Claudia Foray
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Correspondence to Bastian Zinnhardt .

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  1. Department of Radiology, Columbia University Medical Center, New York, NY, USA

    Alexander Birbrair

Appendix

Appendix

Imaging target

Molecular target

Radiotracer

Citation

Tumour-associated macrophages and microglia (TAMMs)

TSPO

[11C]PK11195, [18F]PBR28, [18F]PBR111, [18F]DPA-714, [18F]GE-180

[15,16,17,18,19,20]

CXCR1R

–

[27]

P2X7 and P2Y12

[11C]A-740003, [11C]SMW139, [11C]JNJ-54173717, [11C]GSK1482160, [11C]2

[3, 26, 27]

M2 macrophages

[99mTc]Tc(CO)3-anti-MMR-sdAb, [18F]FB-anti-MMR-sdAbs and [68Ga]Ga-NOTA-anti-MMR-sdAb

[28,29,30]

CSF-1R

[11C]CPPC

[32]

Myeloid-derived suppressor cells

MDSCs (CD11b+ cells)

[99mTc]-labelled anti CD11b antibody, 64Cu-antiCD11b, 89Zr anti-CD11b

[38,39,40]

Tumour-infiltrating lymphocytes

Cancer cell

111In-labelled PD-L1 mAbs, atezolizumab 64Cu and 111In, 89Zr-labelled abs against PD-L1, 89Zr nivolumab and 18F-BMS-986192

[45,46,47,48,49,50,51, 58]

T cells

PD-1 antibody labelled with 64Cu, 64Cu and 89Zr pembrolizumab and nivolumab, 89Zc-Df-nivolumab, IRDye800CW- and 64Cu-labelled liposomes conjugated to PD-1 mAbs, 64Cu-labelled Mb or 89Zr-labelled cDb

[45, 52,53,54,55,56,57, 62,63,64,65,66]

CTLA4 receptor

64Cu-labelled CTLA-4 mAbs, 64Cu-labelled ipilimumab and 89Zr-labelled PEGylated single-domain antibody fragments

[59,60,61]

Neutrophils

Formyl peptide receptor (FPR)

cFLFLFK-PEG-64Cu, 68Ga-NRT-cFLFLF

[73, 74]

Carcinoma-associated fibroblast

Fibroblast-activating protein (FAP)

68Ga-FAPI, 90Y-FAPI

[88,89,90,91]

Vasculature and hypoxia

VEGF receptors

[123I]-VEGF, 89Zr-labelled bevacizumab

[97,98,99]

αvβ3 ligand-binding domain

[18F]Alfatide II, radiolabelled RGD peptides

[95, 103, 104]

Tumour hypoxia

[18F]FMISO

[105,106,107,108]

LAT-1

[11C]MET, [18F]FET, [89Zr]DFO-Ab2

[110,111,112,113]

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Foray, C. et al. (2020). Multimodal Molecular Imaging of the Tumour Microenvironment. In: Birbrair, A. (eds) Tumor Microenvironment. Advances in Experimental Medicine and Biology, vol 1225. Springer, Cham. https://doi.org/10.1007/978-3-030-35727-6_5

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