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Hypoxia-induced gene expression in chemoradioresistant cervical cancer revealed by dynamic contrast enhanced MRI

ABSTRACT: We explored the prognostic impact of the dynamic contrast enhanced MR imaging (DCE-MRI) parameter ABrix in cervical cancer combined with global gene expression data to reveal the underlying molecular phenotype of the parameter and construct a gene signature that reflected ABrix. Based on 78 cervical cancer patients subjected to curative chemoradiotherapy, we identified a prognostic ABrix parameter by pharmacokinetic analysis of DCE-MR images based on the Brix model, where tumors with low ABrix appeared to be most aggressive. Gene set enrichment analysis of 46 tumors with pairwise DCE-MRI and gene expression data showed a significant correlation between ABrix and the hypoxia gene sets, whereas gene sets related to proliferation, radioresistance, and wound healing were not significant. Hypoxia gene sets specific for cervical cancer created in cell culture experiments, including targets of the hypoxia inducible factor (HIF1α) and the unfolded protein response (UPR), were the most significant. In the remaining 32 tumors, low ABrix was associated with upregulation of HIF1α protein expression, as assessed by immunohistochemistry, consistent with increased hypoxia. Based on the hypoxia gene sets, a signature of 31 genes that were upregulated in tumors with low ABrix was constructed. This DCE-MRI hypoxia gene signature showed prognostic impact in an independent validation cohort of 109 patients.

ORGANISM(S): Homo sapiens

PROVIDER: GSE36562 | GEO | 2012/08/16

SECONDARY ACCESSION(S): PRJNA153395

REPOSITORIES: GEO

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Hypoxia-induced gene expression in chemoradioresistant cervical cancer revealed by dynamic contrast enhanced MRI

Project description:We explored the prognostic impact of the dynamic contrast enhanced MR imaging (DCE-MRI) parameter ABrix in cervical cancer combined with global gene expression data to reveal the underlying molecular phenotype of the parameter and construct a gene signature that reflected ABrix. Based on 78 cervical cancer patients subjected to curative chemoradiotherapy, we identified a prognostic ABrix parameter by pharmacokinetic analysis of DCE-MR images based on the Brix model, where tumors with low ABrix appeared to be most aggressive. Gene set enrichment analysis of 46 tumors with pairwise DCE-MRI and gene expression data showed a significant correlation between ABrix and the hypoxia gene sets, whereas gene sets related to proliferation, radioresistance, and wound healing were not significant. Hypoxia gene sets specific for cervical cancer created in cell culture experiments, including targets of the hypoxia inducible factor (HIF1M-NM-1) and the unfolded protein response (UPR), were the most significant. In the remaining 32 tumors, low ABrix was associated with upregulation of HIF1M-NM-1 protein expression, as assessed by immunohistochemistry, consistent with increased hypoxia. Based on the hypoxia gene sets, a signature of 31 genes that were upregulated in tumors with low ABrix was constructed. This DCE-MRI hypoxia gene signature showed prognostic impact in an independent validation cohort of 109 patients. Gene expression correlating with the DCE-MRI parameter ABrix were identified in 46 patients (DCE-MRI cohort) and used to find a hypoxia gene signature. The prognsotic impact of the gene signature was validated in an independent cohort of 109 patients (validation chort). Cell culture experiments were performed to generate cervical cancer specific gene lists associated with hypoxia (GSM897799 - GSM897804).

2012-08-16 | E-GEOD-36562 | biostudies-arrayexpress

MR Imaging Distinguishes Tumor Hypoxia Levels of Different Prognostic and Biological Significance in Cervical Cancer

Project description: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 e 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.

2020-09-01 | GSE147384 | GEO

Integrative analysis of DCE-MRI and gene expression profiles in construction of a gene classifier for assessment of hypoxia-related risk of chemoradiotherapy failure in cervical cancer

Project description:We have previously identified a prognostic 31-gene expression signature in locally advanced cervical cancer that is associated with tumor hypoxia and reflected by the dynamic contrast enhanced magnetic resonance (DCE-MR) image parameter ABrix. To bring the signature closer to clinical use, we here aimed to construct a classifier with key signature genes that retained an association to ABrix and separated the patients into groups with different hypoxia status and chemoradiotherapy outcome. 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 (WG6, HT12), and for a subset of 74 patients, by the RT-qPCR platform. The amplitude ABrix in the Brix pharmacokinetic model was extracted from DCE-MR images of 64 patients and used as a measure of hypoxia. Different classifiers were constructed in the training cohort. By evaluating their ability to separate the patients correctly according to ABrix, a 6-gene classifier with strong correlation to ABrix was identified. In validation analyses, the classifier separated the patients into two groups with 5-years progression-free survival probabilities of 85% and 60%. Both the prognostic value and ABrix-association were confirmed in an independent cohort, and robustness across array generations and assay platforms was demonstrated. The prognostic value was independent of existing clinical markers. A robust, prognostic hypoxia classifier has been constructed, and might be used alone or combined with DCE-MR imaging to achieve an early indication of a patientâs risk of failure and allocate high risk patients to adjuvant hypoxia-targeted therapy. Total 150 patient and 2 cell line samples were analysed with Illumina WG-6, while 136 patient and 6 cell line samples were analyzied with Illumina HT-12.

2016-03-29 | E-GEOD-72723 | biostudies-arrayexpress

Integrative analysis of DCE-MRI and gene expression profiles in construction of a gene classifier for assessment of hypoxia-related risk of chemoradiotherapy failure in cervical cancer

Project description:We have previously identified a prognostic 31-gene expression signature in locally advanced cervical cancer that is associated with tumor hypoxia and reflected by the dynamic contrast enhanced magnetic resonance (DCE-MR) image parameter ABrix. To bring the signature closer to clinical use, we here aimed to construct a classifier with key signature genes that retained an association to ABrix and separated the patients into groups with different hypoxia status and chemoradiotherapy outcome. 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 (WG6, HT12), and for a subset of 74 patients, by the RT-qPCR platform. The amplitude ABrix in the Brix pharmacokinetic model was extracted from DCE-MR images of 64 patients and used as a measure of hypoxia. Different classifiers were constructed in the training cohort. By evaluating their ability to separate the patients correctly according to ABrix, a 6-gene classifier with strong correlation to ABrix was identified. In validation analyses, the classifier separated the patients into two groups with 5-years progression-free survival probabilities of 85% and 60%. Both the prognostic value and ABrix-association were confirmed in an independent cohort, and robustness across array generations and assay platforms was demonstrated. The prognostic value was independent of existing clinical markers. A robust, prognostic hypoxia classifier has been constructed, and might be used alone or combined with DCE-MR imaging to achieve an early indication of a patient’s risk of failure and allocate high risk patients to adjuvant hypoxia-targeted therapy.

2016-03-29 | GSE72723 | GEO

A compact VEGF signature associated with distant metastases and poor outcomes

Project description:Results When compared with each other, primary tumors and regional metastases showed statistically indistinguishable gene expression patterns. Supervised analyses comparing patients with distant metastases versus primary tumors or regional metastases showed that the distant metastases were distinct and distinguished by the lack of expression of fibroblast/mesenchymal genes, and by the high expression of a 13-gene profile (that is, the ‘vascular endothelial growth factor (VEGF) profile’) that included VEGF, ANGPTL4, ADM and the monocarboxylic acid transporter SLC16A3. At least 8 out of 13 of these genes contained HIF1α binding sites, many are known to be HIF1α-regulated, and expression of the VEGF profile correlated with HIF1α IHC positivity. The VEGF profile also showed prognostic significance on tests of sets of patients with breast and lung cancer and glioblastomas, and was an independent predictor of outcomes in primary breast cancers when tested in models that contained other prognostic gene expression profiles and clinical variables. Conclusions These data identify a compact in vivo hypoxia signature that tends to be present in distant metastasis samples, and which portends a poor outcome in multiple tumor types.

2009-03-31 | GSE3521 | GEO

Combining imaging- and gene-based hypoxia biomarkers in cervical cancer improves prediction of treatment failure independent of intratumor heterogeneity

Project description:Emerging biomarkers based on medical images and molecular characterization of tumor biopsies open up for combining the two disciplines and exploiting their synergy in treatment planning. We compared pretreatment classification of cervical cancer patients by two previously validated imaging- and gene-based hypoxia biomarkers, evaluated the influence of intratumor heterogeneity, and investigated the benefit of combining them in prediction of treatment failure. The imaging-based biomarker was hypoxic fraction, determined from diagnostic dynamic contrast enhanced (DCE)-MR images. The gene-based biomarker was a hypoxia gene expression signature determined from tumor biopsies. Paired data were available for 118 patients. Intratumor heterogeneity was assessed by variance analysis of MR images and multiple biopsies from the same tumor. The two biomarkers were combined using a dimension-reduction procedure. The biomarkers classified 75% of the tumors with the same hypoxia status. Both intratumor heterogeneity and distribution pattern of hypoxia from imaging were unrelated to inconsistent classification by the two biomarkers, and the hypoxia status of the slice covering the biopsy region was representative of the whole tumor. Hypoxia by genes was independent on tumor cell fraction and showed minor heterogeneity across multiple biopsies in 9 tumors. This suggested that the two biomarkers could contain complementary biological information. Combination of the biomarkers into a composite score led to improved prediction of treatment failure (HR:7.3) compared to imaging (HR:3.8) and genes (HR:3.0) and prognostic impact in multivariate analysis with clinical variables. In conclusion, combining imaging- and gene-based biomarkers enables more precise and informative assessment of hypoxia-related treatment resistance in cervical cancer, independent of intratumor heterogeneity.

2020-06-26 | GSE146114 | GEO

Selection of reference genes for gene expression studies related to hypoxia in cervical cancer

Project description:The present work aimed to identify reference genes for RT-qPCR studies of hypoxia in 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 treatment in eight cervical cancer cell lines or correlated with the hypoxia-associated dynamic contrast-enhanced magnetic resonance imaging parameter ABrix in 42 patients. Among these genes, we selected 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, for further testing by RT-qPCR. geNorm and NormFinder analyses of RT-qPCR data of 74 patients identified CHCHD1, SRSF9 and TMBIM6 as the most suitable 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 candidates as reference genes were validated in studies of the hypoxia-induced genes DDIT3, ERO1A, and STC2. After normalizing with CHCHD1, SRSF9 and TMBIM6, 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 cervical cancer samples by RT-qPCR. STC2 might be a useful prognostic hypoxia biomarker in cervical cancer that warrants further investigation. Totally 150 tumor samples and 12 cell line samples were analysed with Illumina WG-6 and 4 cell line samples were analysed with Illumina HT-12

2016-03-29 | E-GEOD-75034 | biostudies-arrayexpress

Selection of reference genes for gene expression studies related to hypoxia in cervical cancer

2016-03-29 | GSE75034 | GEO

Identification of interacting proteins of lncRNA HIF1α-AS1

Project description:LncRNA Hypoxia-inducible factor 1α-antisense 1 (HIF1α-AS1) is located on the antisense strand of the important Hypoxia-inducible factor 1α (HIF1α) gene, but being transcribed in antisense direction along the HIF1α promoter. Here we used the 3’end biotinylated HIF1a-AS1 RNA and a control RNA for RNA Pulldown and searched for interacting proteins in nuclear extracts of human umbilical vein endothelial cells (HUVEC).

2022-09-23 | PXD023512 | Pride