Tumor hypoxia levels range from mild to severe and have different biological and therapeutical consequences but are not easily assessable in patients. Here we present a method based on diagnostic dynamic contrast enhanced (DCE) MRI that reflects a continuous range of hypoxia levels in patients with tumors of cervical cancer. Hypoxia images were generated using an established approach based on pixel-wise combination of DCE-MRI parameters n e and K trans , representing oxygen consumption and supply, respectively. Using two tumor models, an algorithm to retrieve surrogate measures of hypoxia levels from the images was developed and validated by comparing the MRI-defined levels with hypoxia levels reflected in pimonidazole-stained histologic sections. An additional indicator of hypoxia levels in patient tumors was established on the basis of expression of nine hypoxia-responsive genes; a strong correlation was found between these indicator values and MRI-defined hypoxia levels in 63 patients. Chemoradiotherapy outcome of 74 patients was most strongly predicted by moderate hypoxia levels, whereas more severe or milder levels were less predictive. By combining gene expression profiles and MRIdefined hypoxia levels in cancer hallmark analysis, we identified a distribution of levels associated with each hallmark; oxidative phosphorylation and G 2 -M checkpoint were associated with moderate hypoxia, epithelial-to-mesenchymal transition, and inflammatory responses with significantly more severe levels. At the mildest levels, IFN response hallmarks together with HIF1A protein expression by IHC appeared significant. Thus, our method visualizes the distribution of hypoxia levels within patient tumors and has potential to distinguish levels of different prognostic and biological significance.Significance: These findings present an approach to image a continuous range of hypoxia levels in tumors and demonstrate the combination of imaging with molecular data to better understand the biology behind these different levels.

Background: Emerging biomarkers from medical imaging or molecular characterization of tumour biopsies open up for combining the two and exploiting their synergy in treatment planning of cancer patients. We generated a paired data set of imaging-and gene-based hypoxia biomarkers in cervical cancer, appraised the influence of intratumour heterogeneity in patient classification, and investigated the benefit of combining the methodologies in prediction of chemoradiotherapy failure. Methods: Hypoxic fraction from dynamic contrast enhanced (DCE)-MR images and an expression signature of six hypoxia-responsive genes were assessed as imaging-and gene-based biomarker, respectively in 118 patients. Findings: Dichotomous biomarker cutoff to yield similar hypoxia status by imaging and genes was defined in 41 patients, and the association was validated in the remaining 77 patients. The two biomarkers classified 75% of 118 patients with the same hypoxia status, and inconsistent classification was not related to imagingdefined intratumour heterogeneity in hypoxia. Gene-based hypoxia was independent on tumour cell fraction in the biopsies and showed minor heterogeneity across multiple samples in 9 tumours. Combining imagingand gene-based classification gave a significantly better prediction of PFS than one biomarker alone. A combined dichotomous biomarker optimized in 77 patients showed a large separation in PFS between more and less hypoxic tumours, and separated the remaining 41 patients with different PFS. The combined biomarker showed prognostic value together with tumour stage in multivariate analysis. Interpretation: Combining imaging-and gene-based biomarkers may enable more precise and informative assessment of hypoxia-related chemoradiotherapy resistance in cervical cancer.

Many patients with locally advanced cervical cancer experience recurrence within the radiation field after chemoradiotherapy. Biomarkers of tumor radioresistance are required to identify patients in need of intensified treatment. Here, the biomarker potential of miR-200 family members was investigated in this disease. Also, involvement of tumor hypoxia in the radioresistance mechanism was determined, using a previously defined 6gene hypoxia classifier. miR-200 expression was measured in pretreatment tumor biopsies of an explorative cohort (n = 90) and validation cohort 1 (n = 110) by RNA sequencing. Publicly available miR-200 data of 79 patients were included for the validation of prognostic significance. A score based on expression of the miR-200a/b/-429 (miR-200a, miR-200b, and miR-429) cluster showed prognostic significance in all cohorts. The score was significant in multivariate analysis of central pelvic recurrence. No association with distant recurrence or hypoxia status was found. Potential miRNA target genes were identified from gene expression profiles and showed enrichment of genes in extracellular matrix organization and cell adhesion. miR-200a/b/-429 overexpression had a pronounced radiosensitizing effect in tumor xenografts, whereas the effect was minor in vitro. In conclusion, miR-200a/b/-429 downregulation is a candidate biomarker of central pelvic recurrence and seems to predict cell adhesion-mediated tumor radioresistance independent of clinical markers and hypoxia.

Tumor hypoxia levels range from mild to severe and have different biological and therapeutical consequences, but are not easily assessable in patients. We present a method based on diagnostic dynamic contrast enhanced (DCE) magnetic resonance imaging (MRI) that visualizes a continuous range of hypoxia levels in tumors of cervical cancer patients. Hypoxia images were generated using an established approach based on pixel-wise combination of the DCE-MRI parameters Ve and Ktrans, reflecting oxygen consumption and supply, respectively. An algorithm to retrieve hypoxia levels from the images was developed and validated in 28 xenograft tumors, by comparing the MRI-defined levels with hypoxia levels derived from pimonidazole stained histological sections. We further established an indicator of hypoxia levels in patient tumors based on expression of nine hypoxia responsive genes. A strong correlation was found between these indicator values and the MRI-defined hypoxia levels in 63 patients. Chemoradiotherapy outcome of 74 patients was most strongly predicted by moderate hypoxia levels, whereas more severe or milder levels were less predictive. By combining gene expression profiles and MRI-defined hypoxia levels in cancer hallmark analysis, we identified a distribution of levels associated with each hallmark; oxidative phosphorylation and G2/M checkpoint were associated with moderate hypoxia, and epithelial-to-mesenchymal transition and inflammatory responses with significantly more severe levels. At the mildest levels, interferon response hallmarks, together with stabilization of HIF1A protein by immunohistochemistry, appearred significant. Thus, our method visualizes the distribution of hypoxia levels within patient tumors and has potential to distinguish levels of different prognostic and biological significance.

Purpose: Emerging biomarkers from medical imaging or molecular characterization of tumor biopsies open up for combining the two and exploiting their synergy in treatment planning. We compared pretreatment classification of locally advanced cervical cancer patients by two previously validated imaging- and gene-based hypoxia biomarkers, appraised the influence of intratumor heterogeneity, and investigated the benefit of combining them in prediction of chemoradiotherapy failure. Experimental Design: Hypoxic fraction, determined from dynamic contrast enhanced (DCE)-MR images, and an expression signature of 6 hypoxia-responsive genes were used as imaging- and gene-based biomarker, respectively, in 118 patients. Intratumor heterogeneity was assessed by variance analysis. The biomarkers were combined using a dimension reduction procedure. Results: The two biomarkers classified 75% of the patients with the same hypoxia status. Inconsistent classification in some cases was not related to imaging-defined intratumor heterogeneity in hypoxia, and hypoxia status of the slice covering the biopsy region was representative of the whole tumor. Hypoxia assessed by gene expression was independent on tumor cell fraction in the biopsies and showed minor heterogeneity across multiple samples in 9 tumors. Inconsistent classification was therefore rather caused by a difference in the hypoxia phenotype reflected by the biomarkers, providing a rational for combining them into a composite score. This score showed improved prediction of treatment failure (HR:7.3) compared to imaging (HR:3.8) and genes (HR:3.0) and significant prognostic impact in multivariate analysis with clinical variables. Conclusion: Combining our imaging- and gene-based biomarkers enables more precise and informative assessment of hypoxia-related chemoradiotherapy resistance in cervical cancer.