American Association for Cancer Research
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Figure 4 from Noninvasive Stratification of Colon Cancer by Multiplex PET Imaging

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posted on 2024-04-15, 07:23 authored by Gaurav Malviya, Tamsin R.M. Lannagan, Emma Johnson, Agata Mackintosh, Robert Bielik, Adam Peters, Dmitry Soloviev, Gavin Brown, Rene Jackstadt, Colin Nixon, Kathryn Gilroy, Andrew Campbell, Owen J. Sansom, David Y. Lewis

Imaging signatures depend on tumor context. A, The generation of mouse models. B, Transverse and coronal PET/MRI slices images showing [18F]FDG uptake in subcutaneous and orthotopic organoid models and GEMM of KrasG12D/+ Trp53fl/fl Rosa26N1icd/+ (KPN) colon cancer. KPN subcutaneous images reproduced here from Fig. 2B for comparison with KPN orthograft and GEMM. Tumors are outlined with a white dotted line. C, Standard uptake peak values (SUVpeak) PET quantification from images in B (n = 4 mice/model). Data compared using ANOVA followed by Fisher least significant difference test. D, Transverse and coronal PET/MRI slices images showing [18F]FDG uptake in subcutaneous and orthotopic KPN and Apcfl/+ KrasG12D/+ Trp53fl/fl Tgfbr1 fl/fl (AKPT) organoid models of colon cancer. Tumors are outlined with a white dotted line. KPN images reproduced here from Figs. 2B and 4B and for comparison to AKPT. E, SUVpeak quantification from images in panel D (Numbers inside bars show sample size, n). Data compared using two-way ANOVA, with the results of injection site shown. Details of all mice used in these studies are presented in Supplementary Table S1. F, Representative GLUT-1 immunohistochemistry of tumors from mice shown in panel E. Black scale bars represents 100 μm. G, H-score of GLUT-1 immunohistochemistry from mice shown in panel E. Box and whisker plots show range, median and interquartile range. Error bars in panel C and E represent standard deviation. Data compared using two-way ANOVA, with the results of injection site shown, * P < 0.05, ** P < 0.01, *** P < 0.001. (A, Created with


Beatson Institute for Cancer Research (The Beatson Institute)

Beatson Cancer Charity



The current approach for molecular subtyping of colon cancer relies on gene expression profiling, which is invasive and has limited ability to reveal dynamics and spatial heterogeneity. Molecular imaging techniques, such as PET, present a noninvasive alternative for visualizing biological information from tumors. However, the factors influencing PET imaging phenotype, the suitable PET radiotracers for differentiating tumor subtypes, and the relationship between PET phenotypes and tumor genotype or gene expression–based subtyping remain unknown. In this study, we conducted 126 PET scans using four different metabolic PET tracers, [18F]fluorodeoxy-D-glucose ([18F]FDG), O-(2-[18F]fluoroethyl)-l-tyrosine ([18F]FET), 3′-deoxy-3′-[18F]fluorothymidine ([18F]FLT), and [11C]acetate ([11C]ACE), using a spectrum of five preclinical colon cancer models with varying genetics (BMT, AKPN, AK, AKPT, KPN), at three sites (subcutaneous, orthograft, autochthonous) and at two tumor stages (primary vs. metastatic). The results demonstrate that imaging signatures are influenced by genotype, tumor environment, and stage. PET imaging signatures exhibited significant heterogeneity, with each cancer model displaying distinct radiotracer profiles. Oncogenic Kras and Apc loss showed the most distinctive imaging features, with [18F]FLT and [18F]FET being particularly effective, respectively. The tissue environment notably impacted [18F]FDG uptake, and in a metastatic model, [18F]FET demonstrated higher uptake. By examining factors contributing to PET-imaging phenotype, this study establishes the feasibility of noninvasive molecular stratification using multiplex radiotracer PET. It lays the foundation for further exploration of PET-based subtyping in human cancer, thereby facilitating noninvasive molecular diagnosis.