Transcriptomics in cancer revealed by Positron Emission Tomography radiomics

Abstract

Metabolic images from Positron Emission Tomography (PET) are used routinely for diagnosis, follow-up or treatment planning purposes of cancer patients. in this study we aimed at determining if radiomic features extracted from 18 F-Fluoro Deoxy Glucose (FDG) PET images could mirror tumor transcriptomics. In this study we analyzed 45 patients with locally advanced head and neck cancer (H&N) that underwent FDG-PET scans at the time of diagnosis and transcriptome analysis using RnAs from both cancer and healthy tissues on microarrays. Association between pet radiomics and transcriptomics was carried out with the Genomica software and a functional annotation was used to associate PET radiomics, gene expression and altered biological pathways. We identified relationships between PET radiomics and genes involved in cell-cycle, disease, DNA repair, extracellular matrix organization, immune system, metabolism or signal transduction pathways, according to the Reactome classification. Our results suggest that these FDG PET radiomic features could be used to infer tissue gene expression and cellular pathway activity in H&n cancers. these observations strengthen the value of radiomics as a promising approach to personalize treatments through targeting tumor-specific molecular processes. 18 F-FDG Positron emission tomography (PET) imaging is largely used for diagnostic purposes in several cancer types, allowing accurate disease staging 1,2 , but it is also gaining ground for therapy applications, including monitoring treatment response and planning in the field of external beam radiotherapy 3. Although visual interpretation may be sufficient for diagnosis, a (semi)quantitative analysis of PET data for image guided therapy applications is most frequently necessary. The simplest parameter usually extracted from PET images used in clinical practice is the maximum standardized uptake value (SUV max) corresponding to the highest single voxel intensity within a region of interest. On the one hand, SUV max has often been reported as a biomarker with potential for improving overall patient management, including the prediction of response to therapy and survival in several cancers 4-6. On the other hand, numerous studies have shown that the predictive/prognostic value of SUV max can be limited, particularly when using images to characterize tumors on baseline PET images 7-9. For this reason, there has been an increasing interest in extracting additional parameters from 18 F-FDG PET images with the objective of more fully characterizing the entire tumor uptake. Most studies initially focused on the delineation of the metabolically active tumor volume (MATV) and associated SUV measurements (such as the mean value or total lesion glycolysis) 10,11 , while more recent studies have concentrated on parameters characterizing the shape or activity distribution within the tumor. These parameters, today known as radiomic features 14 , include 1 st-order image features such as (cumulative) intensity histograms, geometrical tumor shape descriptors...

A Systematic Review of PET Textural Analysis and Radiomics in Cancer

“…We collected information from 60 articles that satisfy our selection criteria and evaluated head and neck cancer [ 28 , 82 , 130 , 131 , 132 , 133 , 134 , 135 , 136 , 137 , 138 , 139 , 140 , 141 , 142 , 143 , 144 , 145 , 146 , 147 , 148 , 149 , 150 , 151 , 152 , 153 , 154 , 155 , 156 , 157 , 158 , 159 , 160 , 161 , 162 , 163 , 164 , 165 , 166 , 167 , 168 , 169 , 170 , 171 , 172 , 173 , 174 , 175 , 176 , ...…”

The Era of Radiogenomics in Precision Medicine: An Emerging Approach to Support Diagnosis, Treatment Decisions, and Prognostication in Oncology

“…In oncology, multimodality imaging, such as positron emission tomography (PET)-computed tomography (CT) and singlephoton emission CT, can describe both the anatomical and functional features of tumors in great detail. However, recent efforts have focused on a combination of quantitative functional assessments, such as multiple PET tracers, various magnetic resonance imaging (MRI) contrast mechanisms, and PET-MRI, thereby revealing multidimensional features of the tumor phenotype (16)(17)(18). For instance, diffusion-weighted MRI is capable of reflecting tumor density and cellularity, and can therefore be used to monitor the response to cytotoxic treatment (19).…”

Radiomic biomarkers of tumor immune biology and immunotherapy response

“…In the largest radiogenomic study to date, Zhu et al reported that CT features such as volume and textural homogeneity were negatively associated with multiple innate and adaptive immune pathways, whereas the same pathways were positively associated with convexity, sphericity, and heterogeneous texture features [73]. In another recent PET radiomics study, immune system pathways were associated with both shape and texture features [74].…”