Hypoxia arises in tumor regions with insufficient oxygen supply and is a major barrier in cancer treatment. The distribution of hypoxia levels is highly heterogeneous, ranging from mild, almost non-hypoxic, to severe and anoxic levels. The individual hypoxia levels induce a variety of biological responses that impair the treatment effect. A stronger focus on hypoxia levels rather than the absence or presence of hypoxia in our investigations will help development of improved strategies to treat patients with hypoxic tumors. Current knowledge on how hypoxia levels are sensed by cancer cells and mediate cellular responses that promote treatment resistance is comprehensive. Recently, it has become evident that hypoxia also has an important, more unexplored role in the interaction between cancer cells, stroma and immune cells, influencing the composition and structure of the tumor microenvironment. Establishment of how such processes depend on the hypoxia level requires more advanced tumor models and methodology. In this review, we describe promising model systems and tools for investigations of hypoxia levels in tumors. We further present current knowledge and emerging research on cellular responses to individual levels, and discuss their impact in novel therapeutic approaches to overcome the hypoxia barrier.

Purpose: A 31-gene expression signature reflected in dynamic contrast enhanced (DCE)-MR images and correlated with hypoxia-related aggressiveness in cervical cancer was identified in previous work. We here aimed to construct a dichotomous classifier with key signature genes and a predefined classification threshold that separated cervical cancer patients into a more and less hypoxic group with different outcome to chemoradiotherapy.Experimental Design: A training cohort of 42 patients and two independent cohorts of 108 and 131 patients were included. Gene expression data were generated from tumor biopsies by two Illumina array generations (WG-6, HT-12). Technical transfer of the classifier to a reverse transcription quantitative PCR (RT-qPCR) platform was performed for 74 patients. The amplitude A Brix in the Brix pharmacokinetic model was extracted from DCE-MR images of 64 patients and used as an indicator of hypoxia.Results: Classifier candidates were constructed by integrative analysis of A Brix and gene expression profiles in the training cohort and evaluated by a leave-one-out cross-validation approach. On the basis of their ability to separate patients correctly according to hypoxia status, a 6-gene classifier was identified. The classifier separated the patients into two groups with different progression-free survival probability. The robustness of the classifier was demonstrated by successful validation of hypoxia association and prognostic value across cohorts, array generations, and assay platforms. The prognostic value was independent of existing clinical markers, regardless of clinical endpoints.Conclusions: A robust DCE-MRI-associated gene classifier has been constructed that may be used to achieve an early indication of patients' risk of hypoxia-related chemoradiotherapy failure.

Loss of 3p11-p14 is a frequent event in epithelial cancer and a candidate prognostic biomarker in cervical cancer. In addition to loss, promoter methylation can participate in gene silencing and promote tumor aggressiveness. We have performed a complete mapping of promoter methylation at 3p11-p14 in two independent cohorts of cervical cancer patients (n = 149, n = 121), using Illumina 450K methylation arrays. The aim was to investigate whether hyperm-ethylation was frequent and could contribute to gene silencing and disease aggressiveness either alone or combined with loss. By comparing the methylation level of individual CpG sites with corresponding data of normal cervical tissue, 26 out of 41 genes were found to be hypermethylated in both cohorts. The frequency of patients with hypermethylation of these genes was found to be higher at tumor stages of 3 and 4 than in stage 1 tumors. Seventeen of the 26 genes were transcriptionally downregulated in cancer compared to normal tissue, whereof 6 genes showed a significant correlation between methylation and expression. Integrated analysis of methylation, gene dosage, and expression of the 26 hypermethylated genes identified 3 regulation patterns encompassing 8 hypermethylated genes; a methylation driven pattern (C3orf14, GPR27, ZNF717), a gene dosage driven pattern (THOC7, PSMD6), and a combined methylation and gene dosage driven pattern (FHIT, ADAMTS9, LRIG1). In survival analysis, patients with both hypermethylation and loss of LRIG1 had a worse outcome compared to those harboring only hypermethylation or none of the events. C3orf14 emerged as a novel methylation regulated suppressor gene, for which knockdown was found to promote invasive growth in human papilloma virus (HPV)-transformed keratinocytes. In conclusion, hypermethylation at 3p11-p14 is common in cervical cancer and may exert a selection pressure during carcinogenesis alone or combined with loss. Information on both events could lead to improved prognostic markers.

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.