4.5 Article

Radiogenomic analysis of primary breast cancer reveals [18F]-fluorodeoxglucose dynamic flux-constants are positively associated with immune pathways and outperform static uptake measures in associating with glucose metabolism

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BREAST CANCER RESEARCH
卷 24, 期 1, 页码 -

出版社

BMC
DOI: 10.1186/s13058-022-01529-9

关键词

Breast cancer; FDG-PET; RNA sequencing; GSEA; Glycolysis; gluconeogenesis; Immune pathways

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资金

  1. Oxford Cancer Imaging Centre - Cancer Research UK
  2. Oxford Cancer Imaging Centre - Engineering and Physical Sciences Research Council [C5255/A16466]
  3. National Institute of Health Research Oxford Biomedical Research Centre
  4. Breast Cancer Research Foundation [BCRF-18-064]
  5. Biotechnology and Biological Research Council [BB/M011224/1]

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In this study, gene set enrichment analysis was performed to identify KEGG pathways associated with FDG uptake in primary breast cancers. Glycolysis/gluconeogenesis pathway and pathways related to immune response or inflammation were found to be associated with FDG uptake. Patlak K, a kinetic parameter, was associated with more pathways than any other imaging index. These results suggest that Patlak analysis of dynamic FDG-PET scans is advantageous for studying tumor biology.
Background PET imaging of 18F-fluorodeoxygucose (FDG) is used widely for tumour staging and assessment of treatment response, but the biology associated with FDG uptake is still not fully elucidated. We therefore carried out gene set enrichment analyses (GSEA) of RNA sequencing data to find KEGG pathways associated with FDG uptake in primary breast cancers. Methods Pre-treatment data were analysed from a window-of-opportunity study in which 30 patients underwent static and dynamic FDG-PET and tumour biopsy. Kinetic models were fitted to dynamic images, and GSEA was performed for enrichment scores reflecting Pearson and Spearman coefficients of correlations between gene expression and imaging. Results A total of 38 pathways were associated with kinetic model flux-constants or static measures of FDG uptake, all positively. The associated pathways included glycolysis/gluconeogenesis ('GLYC-GLUC') which mediates FDG uptake and was associated with model flux-constants but not with static uptake measures, and 28 pathways related to immune-response or inflammation. More pathways, 32, were associated with the flux-constant K of the simple Patlak model than with any other imaging index. Numbers of pathways categorised as being associated with individual micro-parameters of the kinetic models were substantially fewer than numbers associated with flux-constants, and lay around levels expected by chance. Conclusions In pre-treatment images GLYC-GLUC was associated with FDG kinetic flux-constants including Patlak K, but not with static uptake measures. Immune-related pathways were associated with flux-constants and static uptake. Patlak K was associated with more pathways than were the flux-constants of more complex kinetic models. On the basis of these results Patlak analysis of dynamic FDG-PET scans is advantageous, compared to other kinetic analyses or static imaging, in studies seeking to infer tumour-to-tumour differences in biology from differences in imaging. Trial registration NCT01266486, December 24th 2010.

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