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Background: There is significant evidence that DCE-MRI may have the potential to provide clinically useful biomarkers of the outcome of locally advanced cervical carcinoma. However, there is no consensus on how to analyze DCE-MRI data to arrive at the most powerful biomarkers. The purpose of this study was to analyze DCE-MRI data of cervical cancer patients by using the Brix pharmacokinetic model and to compare the biomarkers derived from the Brix analysis with biomarkers determined by non-model-based analysis [i.e., low-enhancing tumor volume (LETV) and tumor volume with increasing signal (TVIS)] of the same patient cohort. Material and methods: DCE-MRI recordings of 80 patients (FIGO stage IB–IVA) treated with concurrent cisplatin-based chemoradiotherapy were analyzed voxel-by-voxel, and frequency distributions of the three parameters of the Brix model (ABrix, kep, and kel) were determined. Moreover, risk volumes were calculated from the Brix parameters and termed RV-ABrix, RV-kep, and RV-kel, where the RVs represent the tumor volume with voxel values below a threshold value determined by ROC analysis. Disease-free survival (DFS) and overall survival (OS) were used as measures of treatment outcome. Results: Significant associations between the median value or any other percentile value of ABrix, kep, or kel and treatment outcome were not found. However, RV-ABrix, RV-kep, and RV-kel correlated with DFS and OS. Multivariate analysis revealed that the prognostic power of RV-ABrix, RV-kep, and RV-kel was independent of well-established clinical prognostic factors. RV-ABrix, RV-kep, and RV-kel correlated with each other as well as with LETV and TVIS. Conclusion: Strong biomarkers of the outcome of locally advanced cervical carcinoma can be provided by subjecting DCE-MRI series to pharmacokinetic analysis using the Brix model. The prognostic power of these biomarkers is not necessarily superior to that of biomarkers identified by non-model-based analyses. [ABSTRACT FROM AUTHOR]

Hypoxia is an adverse factor in cervical cancer, and hypoxia-related gene expression could be a powerful biomarker for identifying the aggressive hypoxic tumors. Reverse transcription quantitative PCR (RT-qPCR) is a valuable method for gene expression studies, but suitable reference genes for data normalization that are independent of hypoxia status and clinical parameters of cervical tumors are lacking. In the present work, we aimed to identify reference genes for RT-qPCR studies of hypoxia in squamous cervical cancer. From 422 candidate reference genes selected from the literature, we used Illumina array-based expression profiles to identify 182 genes not affected by hypoxia in cervical cancer, i.e. genes regulated by hypoxia in eight cervical cancer cell lines or correlating with the hypoxia-associated dynamic contrast-enhanced magnetic resonance imaging parameter ABrix in 42 patients, were excluded. Among the 182 genes, nine candidates (CHCHD1, GNB2L1, IPO8, LASP1, RPL27A, RPS12, SOD1, SRSF9, TMBIM6) that were not associated with tumor volume, stage, lymph node involvement or disease progression in array data of 150 patients, were selected for further testing by RT-qPCR. geNorm and NormFinder analyses of RT-qPCR data of 74 patients identified CHCHD1, SRSF9 and TMBIM6 as the optimal set of reference genes, with stable expression both overall and across patient subgroups with different hypoxia status (ABrix) and clinical parameters. The suitability of the three reference genes were validated in studies of the hypoxia-induced genes DDIT3, ERO1A, and STC2. After normalization, the RT-qPCR data of these genes showed a significant correlation with Illumina expression (P<0.001, n = 74) and ABrix (P<0.05, n = 32), and the STC2 data were associated with clinical outcome, in accordance with the Illumina data. Thus, CHCHD1, SRSF9 and TMBIM6 seem to be suitable reference genes for studying hypoxia-related gene expression in squamous cervical cancer samples by RT-qPCR. Moreover, STC2 is a promising prognostic hypoxia biomarker in cervical cancer. [ABSTRACT FROM AUTHOR]

Background and purpose Several investigators have indicated that dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has the potential to provide biomarkers for personalized treatment of cervical carcinoma. However, some clinical studies have suggested that treatment failure is associated with low tumor signal enhancement, whereas others have reported associations between high signal enhancement and poor outcome. The purpose of this investigation was to clear up these conflicting reports and to provide a method for identifying biomarkers that easily can be implemented in routine DCE-MRI diagnostics. Methods The study involved 85 patients (FIGO stage IB through IVA) treated with concurrent chemoradiotherapy. Low-enhancing tumor volume (LETV) and low-enhancing tumor fraction (LETF), defined as the volume and fractional volume of low-enhancing voxels, respectively, were calculated from signal intensities recorded within 1 min after contrast administration by using two methods reported to give conflicting conclusions. Results Multivariate analysis involving tumor volume, lymph node status, FIGO stage, and LETV or LETF revealed that LETV and LETF provided independent prognostic information on treatment outcome, independent of the method of calculation. Conclusion Low signal enhancement is associated with poor prognosis in cervical carcinoma, and biomarkers predicting poor outcome can be provided by short-term DCE-MRI without advanced image analysis. [ABSTRACT FROM AUTHOR]