Homo sapiens
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ABSTRACT:
PROVIDER: PRJNA294765 | ENA |
REPOSITORIES: ENA
Similar Datasets
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
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 (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.
2012-08-16 | GSE36562 | GEO
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
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
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
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
Project description:Identifying key genes to evaluate the therapeutic responses of chemoradiotherapy. Keywords: Cervical cancer, chemoradiotherapy, biopsy, CDKN1A, Bax
2007-04-30 | GSE3578 | GEO
Project description:Interventions: Single arm prospective observationaI imaging biomarker study.
Patients will have standard treatment, consisting of neoadjuvant chemoradiotherapy followed by surgery. There will be no change to the patient’s treatment by participating in this study. Patients participating in this study will have multi-parametric MRI and PET/CT at the following 3 time-points:
1. Prior to chemoradiotherapy
2. During the third week of chemoradiotherapy
3. Post chemoradiotherapy, within 1 week prior to surgery.
A multi-parametric MRI incorporates standard morphological as well as diffusion weighted imaging and dynamic contrast enhanced sequences.
The total follow-up duration will be 2 years from date of surgery.
Primary outcome(s): Correlation of multi-parametric MRI (diffusion weighted imaging (DWI) and dynamic contrast enhanced (DCE)) at 3 Tesla with surgical histopathology tumour regression grade (TRG).
Histopathological assessment will be performed on surgical specimens. TRG assessment will be performed as per the modified classification of Ryan et al set out in the AJCC Cancer Staging Manual, 7th Edition as follows:
TRG 0 (complete response) - no viable cancer cells
TRG 1 (moderate response) - single cells or small groups of cancer cells
TRG 2 (minimal response) - residual cancer outgrown by fibrosis
TRG 3 (poor response) - minimal or no tumour kill; extensive residual cancer.
[At baseline pre-chemoradiotherapy, week 3 of chemoradiotherapy, and post-chemoradiotherapy (within 1 week prior to surgery) ]
| 2464730 | ecrin-mdr-crc
Project description:Hypoxia-induced gene expression in chemoradioresistant cervical cancer revealed by dynamic contrast enhanced MRI
| PRJNA153395 | ENA
Project description:Patients with cervical cancer were treated with external beam radiotherapy (EBRT) at a dose of 45Gy in 25 fractions over five weeks, with weekly cisplatin. Biopsies were taken pre-, during and post-treatment and analysed for copy number changes. Cervical cancer patients were treated with chemoradiotherapy and disease response was followed by array CGH profiling.
2010-10-25 | E-GEOD-21025 | biostudies-arrayexpress