IDH/MGMT-driven molecular classification of low-grade glioma is a strong predictor for long-term survival

Leu, Severina; von Felten, Stefanie; Fränkl, Stephan; Vassella, Erik; Vajtai, Istvan; Taylor, Elisabeth; Schulz, Marianne; Hutter, Gregor; Hench, Jürgen; Schucht, Philippe; Boulay, Jean-Louis; Mariani, Luigi (2013). IDH/MGMT-driven molecular classification of low-grade glioma is a strong predictor for long-term survival. Neuro-Oncology, 15(4), pp. 469-479. Oxford University Press 10.1093/neuonc/nos317

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BACKGROUND Low-grade gliomas (LGGs) are rare brain neoplasms, with survival spanning up to a few decades. Thus, accurate evaluations on how biomarkers impact survival among patients with LGG require long-term studies on samples prospectively collected over a long period. METHODS The 210 adult LGGs collected in our databank were screened for IDH1 and IDH2 mutations (IDHmut), MGMT gene promoter methylation (MGMTmet), 1p/19q loss of heterozygosity (1p19qloh), and nuclear TP53 immunopositivity (TP53pos). Multivariate survival analyses with multiple imputation of missing data were performed using either histopathology or molecular markers. Both models were compared using Akaike's information criterion (AIC). The molecular model was reduced by stepwise model selection to filter out the most critical predictors. A third model was generated to assess for various marker combinations. RESULTS Molecular parameters were better survival predictors than histology (ΔAIC = 12.5, P< .001). Forty-five percent of studied patients died. MGMTmet was positively associated with IDHmut (P< .001). In the molecular model with marker combinations, IDHmut/MGMTmet combined status had a favorable impact on overall survival, compared with IDHwt (hazard ratio [HR] = 0.33, P< .01), and even more so the triple combination, IDHmut/MGMTmet/1p19qloh (HR = 0.18, P< .001). Furthermore, IDHmut/MGMTmet/TP53pos triple combination was a significant risk factor for malignant transformation (HR = 2.75, P< .05). CONCLUSION By integrating networks of activated molecular glioma pathways, the model based on genotype better predicts prognosis than histology and, therefore, provides a more reliable tool for standardizing future treatment strategies.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Department of Head Organs and Neurology (DKNS) > Clinic of Ophthalmology
04 Faculty of Medicine > Department of Head Organs and Neurology (DKNS) > Clinic of Neurosurgery
04 Faculty of Medicine > Service Sector > Institute of Pathology

UniBE Contributor:

Fränkl, Stephan; Vassella, Erik; Vajtai, Istvan and Schucht, Philippe

Subjects:

600 Technology > 610 Medicine & health
500 Science > 570 Life sciences; biology

ISSN:

1523-5866

Publisher:

Oxford University Press

Language:

English

Submitter:

Nicole Söll

Date Deposited:

09 Dec 2013 16:03

Last Modified:

09 Dec 2013 16:03

Publisher DOI:

10.1093/neuonc/nos317

PubMed ID:

23408861

Uncontrolled Keywords:

biomarker, brain tumor, cancer pathways, prognosis

URI:

https://boris.unibe.ch/id/eprint/39247

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