Multicenter imaging outcomes study of The Cancer Genome Atlas glioblastoma patient cohort: imaging predictors of overall and progression-free survival

Wangaryattawanich, Pattana; Hatami, Mehdi; Wang, Jixin; Thomas, Ginu; Flanders, Adam E.; Kirby, Justin; Wintermark, Max; Huang, Erich; Bakhtiari, Ali Shojaee; Luedi, Markus M.; Hashmi, Syed; Rubin, Daniel L.; Chen, James Y.; Hwang, Scott N.; Freymann, John; Holder, Chad A.; Zinn, Pascal O.; Colen, Rivka R.

doi:10.1093/neuonc/nov117

Cited by 86 publications

(72 citation statements)

References 38 publications

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“…MR images of TCGA cohort have been obtained from The Cancer Imaging Archive (TCIA) website 17,34,35 . We excluded cases with any evidence of prior neurosurgical intervention except biopsy, lack of treatment history, or loss of T1CE or FLAIR/T2 images.…”

Section: Methodsmentioning

confidence: 99%

Spatiotemporal genomic architecture informs precision oncology in glioblastoma

et al. 2017

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Precision medicine in cancer proposes that genomic characterization of tumors can inform personalized targeted therapies1–5. This proposition, however, is complicated by spatial and temporal heterogeneity6–14. Here we study genomic and expression profiles across 127 multi-sector or longitudinal specimens from 52 glioblastoma (GBM) patients. Using bulk and single-cell data, we find that samples from the same tumor mass share genomic and expression signatures, while geographically separated multifocal tumors and/or long-term recurrent tumors are seeded from different clones. Chemical screening of patient-derived glioma cells (PDCs) shows that therapeutic response is associated to genetic similarity, and multifocal tumors enriched with PIK3CA mutations have a heterogeneous drug response pattern. Importantly, we show that targeting truncal events is more efficacious in reducing tumor burden. In summary, this work demonstrates that evolutionary inference from integrated genomic analysis in multi-sector biopsies can inform targeted therapeutic interventions for GBM patients.

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Section: Methodsmentioning

confidence: 99%

Spatiotemporal genomic architecture informs precision oncology in glioblastoma

et al. 2017

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“…The MRI scans were interpreted by two neuroradiologists blinded to the patient outcome. We selected eight cardinal tumor‐related imaging features and dichotomized these features according to previous guidelines using the following criteria: ADC value,12, 13 peritumoral edema,14 contrast‐enhancing tumor (CET),15 necrosis,16 formation of cysts (cyst),16 noncontrast‐enhancing tumor (nCET),17 T1/Flair ratio,16 and deep white matter invasion 15. The exact dichotomy information is listed in Table 1.…”

Section: Methodsmentioning

confidence: 99%

The TERT promoter mutation status and MGMT promoter methylation status, combined with dichotomized MRI‐derived and clinical features, predict adult primary glioblastoma survival

et al. 2018

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PurposeThis study aimed to integrate the TERT promoter mutation status, MGMT promoter methylation status, MRI‐derived features, and clinical features into a survival analysis model to better understand adult primary glioblastoma prognosis‐related markers.MethodA total of 304 adult glioblastoma samples collected after surgical resection were selected for retrospective analysis, and Sanger sequencing was performed to detect IDH and TERT promoter mutations. The methylation of the MGMT promoter was analyzed by pyrosequencing, and MRI‐derived and clinical features were dichotomized into easily acquired variables. Random survival forest analysis, Kaplan‐Meier analysis, Cox proportional hazard regression, and LASSO regression were performed for the survival analysis, and ROC analysis and Pearson's chi‐squared test were employed for the correlation analysis.ResultsWild‐type IDH was present in 89.8% of the adult glioblastoma samples, and TERT promoter mutations and MGMT promoter methylation were observed in 66.42% and 38.49% of all adult primary glioblastomas, respectively. Age and MGMT promoter methylation were identified as independent prognostic biomarkers, and the TERT promoter mutation status and MGMT promoter methylation status, when combined with other tumor‐related factors, generated several different survival subgroups. None of the factors investigated in this study predicted the MGMT promoter status, and MRI‐detected necrosis was positively associated with TERT promoter mutations.ConclusionMGMT promoter methylation and TERT promoter mutations, combined with MRI‐derived and clinical features, revealed different survival subgroups with distinct responses to current treatments, and this information increases the ability to predict the survival of adult primary glioblastoma patients. MRI‐detected necrosis often indicates the presence of TERT promoter mutations.

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“…This differs from the work presented in this study whereby quantitative rather than categorical volumetric assessment was performed, by a single radiologist using a technique, which has previously shown good intra and inter-observer variability [14], and the surrounding T2 signal abnormality/oedema was not included in the whole tumour volume. A larger quantitative volumetric analysis of 94 GBM by the same group also reported increased proportional enhancement was associated with increased mortality (p=0.003), but as with the previously study included the perilesional T2 and FLAIR signal abnormality as part of the whole tumour volume [30]. PerezBeteta et al assessed the pre-treatment geometry in 117 patients with GBM and reported both increases in tumour volume and contrast enhancing volume were associated with reduced overall survival (p=0.034, hazards ratio 1.574 and p=0.017, hazards ratio 1.659), but no assessment of the proportional enhancement of the tumour was made in this study [31].…”

Section: Parametermentioning

confidence: 63%