PET imaging can distinguish different colon subcutaneous organoid cancer models and individual driver genes. A, The data processing workflow for comparing PET radiotracer discriminatory power and the model/gene uniqueness. B, Separation matrix and statistics of the area under the ROC curves for each tracer and model. C, Red highlighted box showing boxplot and ROC curves for [18F]FDG in the BMT (n = 6 subcutaneous organoid allografts) compared with other models (n = 19), each point represents a mouse. Numbers inside bars show sample size, n. Data compared using unpaired t test. D, Separation matrix and statistics of the area under the ROC curves for each tracer and gene. Tgfbr1/Alk5 fl/fl and Tgfbr2 fl/fl are combined as TGFb for this analysis. E, Red highlighted box showing boxplot and ROC curves for [18F]FLT in the Kras (n = 18) compared to other subcutaneous models (n = 6), each point represents a mouse. Numbers inside bars show n. Data compared using unpaired t test. Error bars in C and D represent SD. *, P < 0.05; **, P < 0.01; ***, P < 0.001 for unpaired t tests and AUC ROC. Each analysis stands on its own; no multiple comparison testing was used. See extended datasets in Supplementary Fig. S4. (A, Created with BioRender.com.)
ARTICLE ABSTRACT
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.
