18F-Fluorodeoxy-glucose Positron Emission Tomography Marks MYC-Overexpressing Human Basal-Like Breast Cancers

Abstract

In contrast to normal cells, cancer cells avidly take up glucose and metabolize it to lactate even when oxygen is abundant, a phenomenon referred to as the Warburg effect. This fundamental alteration in glucose metabolism in cancer cells enables their specific detection by Positron Emission Tomography (PET) following intravenous injection of the glucose analogue 18F-fluorodeoxy-glucose (18FDG). However, this useful imaging technique is limited by the fact that not all cancers avidly take up FDG. To identify molecular determinants of 18FDG-retention, we interogated the transcriptomes of human cancer cell lines and primary tumors for metabolic pathways associated with 18FDG radiotracer uptake. From 95 metabolic pathways that were interrogated, the glycolysis and several glycolysis-related pathways (pentose-phosphate, carbon fixation, aminoacyl-tRNA biosynthesis, one-carbon-pool by folate) showed the greatest transcriptional enrichment. This “FDG signature” predicted FDG-uptake in breast cancer cell lines and overlapped with established gene expression signatures for the “basal-like” breast cancer subtype and MYC-induced tumorigenesis in mice. Human breast cancers with nuclear MYC staining and high RNA expression of MYC target genes showed high 18FDG-PET uptake (p < 0.005). Presence of the FDG signature was similarly associated with MYC gene copy gain, increased MYC transcript levels, and elevated expression of metabolic MYC target genes in a human breast cancer genomic dataset. Together, our findings link clinical observations of glucose uptake with a pathologic and molecular subtype of human breast cancer. Further, they suggest related approaches to derive molecular determinants of radiotracer retention for other PET-imaging probes.

Imaging genomics in cancer research: limitations and promises

“…8 studies used data from The Cancer Genome Atlas (TCGA) and/or The Cancer Imaging Archive (TCIA); 1,16,23,27,32,34,38,41 2 studies were multi-institutional; 9,19 and the remaining 17 studies used local institutional data. 15,17,18,[20][21][22][24][25][26]28,30,31,33,[35][36][37]39,40 26 out of 27 studies were retrospective in design. The number of patients ranged from 10 to 104 patients, with a median of 38 patients.…”

“…8 (30%) studies used a validation data set to verify the association between imaging features and genomic data identified in the initial data set. 20,22,23,27,28,34,37,40 Six types of cancers were studied: glioblastoma multiforme (GBM)/high-grade glioma (n 5 14, 52%), non-small-cell lung cancer (NSCLC) (n 5 3, 11%), hepatocellular carcinoma (HCC) (n 5 3, 11%), breast cancer (n 5 5, 19%), clear-cell renal cell carcinoma (CCRCC) (n 5 1, 4%) and cervical cancer (n 5 1, 4%). The imaging modalities used included fluorine 18 fludeoxyglucose positron emission tomography (PET) (n 5 4, 15%), MRI [n 5 18 (including two perfusion MR), 67%] and CT [n 5 5 (including one perfusion CT), 19%].…”

Coordination of Nutrient Availability and Utilization by MAX- and MLX-Centered Transcription Networks

“…), thus it will be of interest to determine whether this regulatory mechanism correlates exclusively with MYC status or whether other regulators also contribute. Triple negative breast cancers have high MYC levels, high rates of aerobic glycolysis, a glycolytic gene signature, and express glutaminase (Chandriani et al 2009;Foulkes et al 2010;Palaskas et al 2011;Horiuchi et al 2012). Consistent with these findings, triple negative breast cancers are more dependent on glutamine for growth than luminal cancers (Kung et al 2011).…”

Radiogenomics and Radioproteomics

“…This rationale has been explored in research but no attempt to investigate a clinical application has been initiated. A small amount of work has already been initiated looking more specifically at radiogenomics/radioproteomics in tumors [2][3][4][5][6][7][8][9], as well as prognosis and therapy modulation. Fukuda et al showed a significant negative correlation between the metabolic rate of oxygen and Fluorodeoxyglucose (FDG) standardized uptake value (SUV) in human liver tumors [10].…”

“…Dooms et al on the other hand found that the percentage of viable tumor cells and Ki-67 length density after induction chemotherapy were significantly lower in metabolic responders compared with non-responders [11]. Palsakas et al identified an "FDG signature" in the basal subtype of breast cancer and correlated that with the over expression of the transcription factor c-MYC [9]. His group identified a higher FDG score for this subtype of breast cancer.…”