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Comparison of MRI with histology, construction of hypoxia images, and hypoxia levels in patients

Comparing classification based on ABrix and 6-gene classifier.

Transformation of data from Illumina HT-12 and RT-qPCR assays to Illumina WG-6 scale.

DCE-MRI and digital histopathology

Validation of algorithm for assessing hypoxia levels in patient tumors

Comparing our 6 classifier genes with published hypoxia gene signatures.

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 ABrix 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 ABrix 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. Clin Cancer Res; 22(16); 4067–76. ©2016 AACR.

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 νe and Ktrans, 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 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, 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.

Construction of a hypoxia gene classifier.

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 νe and Ktrans, 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 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, 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.

CDK regulatory subunit 2 (CKS2) has a nuclear function that promotes cell division and is a candidate biomarker of chemoradioresistance in cervical cancer. The underlying mechanisms are, however, not completely understood. We investigated whether CKS2 also has a mitochondrial function that augments tumor aggressiveness. Based on global gene expression data of two cervical cancer cohorts of 150 and 135 patients, we identified a set of genes correlated with CKS2 expression. Gene set enrichment analysis showed enrichment of mitochondrial cellular compartments, and the hallmarks oxidative phosphorylation (OXPHOS) and targets of the MYC oncogene in the gene set. By in situ proximity ligation assay, we showed that CKS2 formed complex with the positively correlated MYC target, mitochondrial single-stranded DNA binding protein SSBP1, in the mitochondrion of cervix tumor samples and HeLa and SiHa cervical cancer cell lines, indicating a role in mitochondrial DNA (mtDNA) replication and thereby OXPHOS. CDK1 was found to be part of the complex. Flow cytometry analyses of HeLa cells showed cell cycle regulation of the CKS2-SSBP1 complex consistent with mtDNA replication activity. Moreover, repression of mtDNA replication and OXPHOS by acute hypoxia decreased CKS2-SSBP1 complex abundance and expression of MYC targets. By immunohistochemistry, cytoplasmic CKS2 expression was found to add to the prognostic impact of nuclear CKS2 expression in patients, suggesting that the mitochondrial function promotes tumor aggressiveness. Our study uncovers a novel link between regulation of cell division by nuclear pathways and OXPHOS in the mitochondrion that involves CKS2 and promotes chemoradioresistance of cervical cancer.

Simple Summary Hypoxia is a common feature of solid tumors and associated with poor outcome in most cancer types and treatment modalities, including radiotherapy, chemotherapy, surgery and, most likely, immunotherapy. Emerging strategies, such as proton therapy and combination therapies with radiation and hypoxia targeted drugs, provide new opportunities to overcome the hypoxia barrier and improve therapeutic outcome. Hypoxia is heterogeneously distributed both between and within tumors and shows large variations across patients not only in prevalence, but importantly, also in level. To best exploit the emerging strategies, a better understanding of how individual hypoxia levels from mild to severe affect tumor biology is vital. Here, we discuss our current knowledge on this topic and how we should proceed to gain more insight into the field. Abstract 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.

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 imaging-defined 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 imaging- and 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. Funding Norwegian Cancer Society, South-Eastern Norway Regional Health Authority, and Norwegian Research Council.

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 parametersνeandKtrans, 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.

Human papillomavirus (HPV)-associated cervical cancer represents one of the leading causes of cancer death worldwide. Although low-middle income countries are disproportionately affected, our knowledge of the disease predominantly originates from populations in high-income countries. Using the largest multi-omic analysis of cervical squamous cell carcinoma (CSCC) to date, totalling 643 tumours and representing patient populations from the USA, Europe and Sub-Saharan Africa, we identify two CSCC subtypes (C1 and C2) with differing prognosis. C1 tumours are largely HPV16-driven, display increased cytotoxic T-lymphocyte infiltration and frequently harbour PIK3CA and EP300 mutations. C2 tumours are associated with shorter overall survival, are frequently driven by HPVs from the HPV18-containing alpha-7 clade, harbour alterations in the Hippo signalling pathway and increased expression of immune checkpoint genes, B7-H3 (also known as CD276) and NT5E (also known as CD73) and PD-L2 (also known as PDCD1LG2). In conclusion, we identify two novel, therapy-relevant CSCC subtypes that share the same defining characteristics across three geographically diverse cohorts.

Hypoxia is a generic micro-environmental factor in most solid tumours. While most published literature focused on in vitro or single tumour type investigations, we carried out the first multi-omics pan cancer analysis of hypoxia with the aim of gaining a comprehensive understanding of its implication in tumour biology. A core set of 52 mRNAs were curated based on experimentally validated hypoxia gene sets from multiple cancer types. The 52 mRNAs collectively stratified high- and low-hypoxia tumours from The Cancer Genome Atlas (TCGA) database (9698 primary tumours) in each of the 32 cancer types available. High- hypoxia tumours had high expression of not only mRNA but also protein and microRNA markers of hypoxia. In a pan cancer transcriptomic analysis, ≥70% of the known cancer hallmark pathways were enriched in high-hypoxia tumours, most notably epithelial mesenchymal transition potential, proliferation (G2M checkpoint, E2F targets, MYC targets) and immunology response. In a multi-omics analysis, gene expression-determined high- hypoxia tumours had a higher non-silent mutation rate, DNA damage repair deficiency and leukocyte infiltration. The associations largely remained significant after correcting for confounding factors, showing a profound impact of hypoxia in tumour evolution across cancer types. High-hypoxia tumours determined using the core gene set had a poor prognosis in 16/32 cancer types, with statistical significances remaining in five after adjusting for tumour stage and omics biomarkers. In summary, this first comprehensive in vivo map of hypoxia in cancers highlights the importance of this micro-environmental factor in driving tumour progression.

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

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 ABrix 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 ABrix 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. Clin Cancer Res; 22(16); 4067–76. ©2016 AACR.

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.