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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 ¹⁸F-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.

SUBMITTER: Tixier F

PROVIDER: S-EPMC7101432 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Transcriptomics in cancer revealed by Positron Emission Tomography radiomics.

Tixier Florent F Cheze-le-Rest Catherine C Schick Ulrike U Simon Brigitte B Dufour Xavier X Key Stéphane S Pradier Olivier O Aubry Marc M Hatt Mathieu M Corcos Laurent L Visvikis Dimitris D

Scientific reports 20200327 1

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 <sup>18</sup>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 b ...[more]

PMID: 32221360

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Project description:Radiomics studies require large patient cohorts, which often include patients imaged using different imaging protocols. We aimed to determine the impact of variability in imaging protocol parameters and interscanner variability using a phantom that produced feature values similar to those of patients. Positron emission tomography (PET) scans of a Hoffman brain phantom were acquired on GE Discovery 710, Siemens mCT, and Philips Vereos scanners. A standard-protocol scan was acquired on each machine, and then each parameter that could be changed was altered individually. The phantom was contoured with 10 regions of interest (ROIs). Values for 45 features with 2 different preprocessing techniques were extracted for each image. To determine the impact of each parameter on the reliability of each radiomics feature, the intraclass correlation coefficient (ICC) was calculated with the ROIs as the subjects and the parameter values as the raters. For interscanner comparisons, we compared the standard deviation of each radiomics feature value from the standard-protocol images to the standard deviation of the same radiomics feature from PET scans of 224 patients with non-small cell lung cancer. When the pixel size was resampled prior to feature extraction, all features had good reliability (ICC > 0.75) for the field of view and matrix size. The time per bed position had excellent reliability (ICC > 0.9) on all features. When the filter cutoff was restricted to values below 6 mm, all features had good reliability. Similarly, when subsets and iterations were restricted to reasonable values used in clinics, almost all features had good reliability. The average ratio of the standard deviation of features on the phantom scans to that of the NSCLC patient scans was 0.73 using fixed-bin-width preprocessing and 0.92 using 64-level preprocessing. Most radiomics feature values had at least good reliability when imaging protocol parameters were within clinically used ranges. However, interscanner variability was about equal to interpatient variability; therefore, caution must be used when combining patients scanned on equipment from different vendors in radiomics data sets.

Project description:Fluorine-18-fluoro-2-deoxy-D-glucose (FDG) is widely used as positron-emission-tomography (PET) radiotracer for the detection and staging of human cancer. Tumor uptake of FDG varies substantially between different cancer types and between patients with the same tumor type. The molecular basis for this heterogeneity is unknown. Using cancer cell lines and primary human tumors of distinct histologic origins, we here show that increased FDG uptake is universally associated with coordinate upregulation of genes within the glycolysis, pentose-phosphate, and other related metabolic pathways. In primary human breast cancers, this FDG signature shows significant overlap with established breast cancer signatures for the “basal-like” disease subtype and “poor prognosis”. FDG high breast cancer showed significantly more gene copy number alterations genome wide than FDG low cancers. About 50 % of primary breast cancers with high FDG uptake and FDG gene expression signature show DNA copy gain encompassing the c-myc gene locus and express gene sets regulated by the transcription factor MYC. Our data shows that FDG-PET marks a distinct subset of “basal-like” human breast cancer which is characterized by MYC and prognostically unfavorable gene expression signatures, suggesting that FDG-PET imaging may be useful to risk-stratify patients with locally advanced breast cancer. Our general strategy to identify molecular determinants of FDG-retention through a genome-wide approach consisted of FDG uptake measurements in cancer cell lines and primary human tumors, the selection of samples with particularly high versus low FDG-retention, and subsequent pathway-based analysis of RNA expression data collected from these samples. Cell line RNA was extracted from a 10 cm plate seeded simultaneously and at the same density as the wells for FDG-uptake assays. For primary human tumor samples, RNA was extracted from macrodissected frozen tumor tissue. All cell line RNA samples and the astrocytoma RNA aliquots were hybridized to Affymetrix U133 Plus 2.0 arrays. All primary breast cancer RNA samples were hybridized to Affymetrix U133A arrays.

Dataset Information

Transcriptomics in cancer revealed by Positron Emission Tomography radiomics.

Publications

Transcriptomics in cancer revealed by Positron Emission Tomography radiomics.

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