ArticleCancer medicine2018
Molecular profiles of tumor contrast enhancement: A radiogenomic analysis in anaplastic gliomas.
Article in Cancer medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Radiogenomic landscape of the hallmarks of cancer.Biomarker research · 2026Review
- From Images to Genes: Radiogenomics Based on Artificial Intelligence to Achieve Non-Invasive Precision Medicine in Cancer Patients.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Review
- Radiomics for characterization of the glioma immune microenvironment.NPJ precision oncology · 2023Review
- Predicting isocitrate dehydrogenase genotype, histological phenotype, and Ki-67 expression level in diffuse gliomas with an advanced contrast analysis of magnetic resonance imaging sequences.Quantitative imaging in medicine and surgery · 2023Article
- Review
- Assessing Versatile Machine Learning Models for Glioma Radiogenomic Studies across Hospitals.Cancers · 2021Article
- Radiomic biomarkers of tumor immune biology and immunotherapy response.Clinical and translational radiation oncology · 2021Review
- Imaging-Genomics in Glioblastoma: Combining Molecular and Imaging Signatures.Frontiers in oncology · 2021Review
- Preoperative Radiomics Analysis of 1p/19q Status in WHO Grade II Gliomas.Frontiers in oncology · 2021Article
- Patient‑derived orthotopic xenograft glioma models fail to replicate the magnetic resonance imaging features of the original patient tumor.Oncology reports · 2020Article
- Molecular profiles of tumor contrast enhancement: A radiogenomic analysis in anaplastic gliomas.Cancer medicine · 2018Article
Corrections and comments
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Authors and funding
10 authors.
Funding
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Abstract
The presence of contrast enhancement (CE) on magnetic resonance (MR) imaging is conventionally regarded as an indicator for tumor malignancy. However, the biological behaviors and molecular mechanism of enhanced tumor are not well illustrated. The aim of this study was to investigate the molecular profiles associated with anaplastic gliomas (AGs) presenting CE on postcontrast T1-weighted MR imaging. In this retrospective database study, RNA sequencing and MR imaging data of 91 AGs from the Cancer Genome Atlas (TCGA) and 64 from the Chinese Glioma Genome Atlas (CGGA) were collected. Gene set enrichment analysis (GSEA), significant analysis of microarray, generalized linear models, and Least absolute shrinkage and selection operator algorithm were used to explore radiogenomic and prognostic signatures of AG patients. GSEA indicated that angiogenesis and epithelial-mesenchymal transition were significantly associated with post-CE. Genes driving immune system response, cell proliferation, and focal adhesions were also significantly enriched. Gene ontology of 237 differential genes indicated consistent results. A 48-gene signature for CE was identified in TCGA and validated in CGGA dataset (area under the curve = 0.9787). Furthermore, seven genes derived from the CE-specific signature could stratify AG patients into two subgroups based on overall survival time according to corresponding risk score. Comprehensive analysis of post-CE and genomic characteristics leads to a better understanding of radiology-pathology correlations. Our gene signature helps interpret the occurrence of radiological traits and predict clinical outcomes. Additionally, we found nine prognostic quantitative radiomic features of CE and investigated the underlying biological processes of them.
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