Hypoxia-Induced Gene Expression in Chemoradioresistant Cervical Cancer Revealed by Dynamic Contrast-Enhanced MRI

Abstract

Knowledge of the molecular background of functional magnetic resonance (MR) images is required to fully exploit their potential in cancer management. We explored the prognostic impact of dynamic contrastenhanced MR imaging (DCE-MRI) parameters in cervical cancer combined with global gene expression data to reveal their underlying molecular phenotype and construct a representative gene signature for the relevant parameter. On the basis of 78 patients with cervical cancer subjected to curative chemoradiotherapy, we identified the prognostic DCE-MRI parameter A Brix by pharmacokinetic analysis of pretreatment images based on the Brix model, in which tumors with low A Brix appeared to be most aggressive. Gene set analysis of 46 tumors with pairwise DCE-MRI and gene expression data showed a significant correlation between A Brix and the hypoxia gene sets, whereas gene sets related to other tumor phenotypes were not significant. Hypoxia gene sets specific for cervical cancer created in cell culture experiments, including both targets of the hypoxia inducible factor (HIF1a) and the unfolded protein response, were the most significant. In the remaining 32 tumors, low A Brix was associated with upregulation of HIF1a protein expression, as assessed by immunohistochemistry, consistent with increased hypoxia. On the basis of the hypoxia gene sets, a signature of 31 genes that were upregulated in tumors with low A Brix was constructed. This DCE-MRI hypoxia gene signature showed prognostic impact in an independent validation cohort of 109 patients. Our findings reveal the molecular basis of an aggressive hypoxic phenotype and suggest the use of DCE-MRI to noninvasively identify patients with hypoxia-related chemoradioresistance. Cancer Res; 72(20); 5285-95. Ó2012 AACR.

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%].…”

“…22,25,26,37,40 Two studies performed quantitative polymerase chain reaction (PCR) to verify the significant difference in gene expression among imaging phenotypes through association studies. 22,26 Two studies performed gene expression analysis in corresponding cancer cell lines.…”

“…22,26 Two studies performed gene expression analysis in corresponding cancer cell lines. 37,40 One study performed immunological staining of epidermal growth factor receptor (EGFR) and found differentially expressed EGFR among different imaging phenotypes. 25 Semi-radiogenomic studies 38 semi-radiogenomic studies were identified (Table 4).…”

Potential role of increased oxygenation in altering perinatal adrenal steroidogenesis

“…In addition, the mRNAs for 3 other genes were increased and 11 were decreased after 1 d of normoxia and 61 mRNAs were increased and 60 reduced after 2 d of normoxia. Among the genes whose mRNAs increased or decreased under normoxic conditions (Tables 1 and 2), ALDOA, ALDOC, BNIP3, BNIP3L, CA9, ENO1, GADPH, HK2, IGFBP2, JMJD1A, LDHA, NDRG1, PKM2, SLC2A1, SLC2A3, and TPI1 are known to be transcriptionally regulated by hypoxia (24). Only four genes, BNIP3, NDRG1, SERPINA3, and SLC2A1 were regulated in common in both NCI-H295A cells and in the primary culture of fetal adrenal cells.…”