Molecular profiles of tumor contrast enhancement: A radiogenomic analysis in anaplastic gliomas

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.

Magnetic resonance perfusion image features uncover an angiogenic subgroup of glioblastoma patients with poor survival and better response to antiangiogenic treatment

Background

In previous clinical trials, antiangiogenic therapies such as bevacizumab did not show efficacy in patients with newly diagnosed glioblastoma (GBM). This may be a result of the heterogeneity of GBM, which has a variety of imaging-based phenotypes and gene expression patterns. In this study, we sought to identify a phenotypic subtype of GBM patients who have distinct tumor-image features and molecular activities and who may benefit from antiangiogenic therapies.

Methods

Quantitative image features characterizing subregions of tumors and the whole tumor were extracted from preoperative and pretherapy perfusion magnetic resonance (MR) images of 117 GBM patients in 2 independent cohorts. Unsupervised consensus clustering was performed to identify robust clusters of GBM in each cohort. Cox survival and gene set enrichment analyses were conducted to characterize the clinical significance and molecular pathway activities of the clusters. The differential treatment efficacy of antiangiogenic therapy between the clusters was evaluated.

Results

A subgroup of patients with elevated perfusion features was identified and was significantly associated with poor patient survival after accounting for other clinical covariates (P values <.01; hazard ratios > 3) consistently found in both cohorts. Angiogenesis and hypoxia pathways were enriched in this subgroup of patients, suggesting the potential efficacy of antiangiogenic therapy. Patients of the angiogenic subgroups pooled from both cohorts, who had chemotherapy information available, had significantly longer survival when treated with antiangiogenic therapy (log-rank P=.022).

Conclusions

Our findings suggest that an angiogenic subtype of GBM patients may benefit from antiangiogenic therapy with improved overall survival.

Integrative radiogenomic analysis for genomic signatures in glioblastomas presenting leptomeningeal dissemination

Despite therapeutic advances, the prognosis for glioblastoma (GBM) remains poor. In particular, leptomeningeal dissemination (LMD) has a dismal prognosis. The aim of this study was to identify tumor molecular phenotype, which has a great propensity to develop LMD. Between May 2004 and December 2012, a total of 145 GBM tumor samples were obtained from data registry. A total of 20 of the 145 patients with GBM were found to develop LMD. A specialized radiologist confirmed the diagnosis of LMD on magnetic resonance imaging. To clarify the genomic signatures in GBM with LMD, we performed integrative analysis of whole transcriptome sequencing and copy number alteration in the radiological features indicating LMD phenotypes in GBM. Eleven newly diagnosed patients with GBM with LMD had worse prognosis than those without LMD (median 5.55 vs. 12.94 months, P < 0.0001). Integrating analysis using gene expression based on the change of copy number revealed that SPOCK1, EHD2, SLC2A3, and ANXA11 were highly expressed with the gain of copy number, compared with the gene expression in the non-LMD group. In addition, it was demonstrated that NME2, TMEM100, and SIVA1 were downregulated with the loss of copy number. We also found that mesenchymal subtype accounted for 50% in LMD group, whereas mesenchymal subtype consisted of 29% in non-LMD group, even though there was no statistical significance (P = 0.06). Through this radiogenomic analysis, we suggested the possibility of finding candidate genes associated with LMD and highlighted the significance of integrating approach to clarify the molecular characteristics in LMD.