Radical surgical resection with molecular margins is associated with improved survival in IDH wild-type glioblastoma

Abstract

Background: Survival is variable in patients with glioblastoma IDH wild-type (GBM), even after comparable surgical resection of radiographically detectable disease, highlighting the limitations of radiographic assessment of infiltrative tumor anatomy. The majority of postsurgical progressive events are failures within 2 cm of the resection margin, motivating supramaximal resection strategies to improve local control. However, which patients benefit from such radical resections remains unknown.

Methods: We developed a predictive model to identify which IDH wild-type GBMs are amenable to radiographic gross-total resection (GTR). We then investigated whether GBM survival heterogeneity following GTR is correlated with microscopic tumor burden by analyzing tumor cell content at the surgical margin with a rapid qPCR-based method for detection of TERT promoter mutation.

Results: Our predictive model for achievable GTR, developed on retrospective radiographic and molecular data of GBM patients undergoing resection, had an area under the curve of 0.83, sensitivity of 62%, and specificity of 90%. Prospective analysis of this model in 44 patients found that 89% of patients were correctly predicted to achieve a residual volume (RV) < 4.9cc. Of the 44 prospective patients undergoing rapid qPCR TERT promoter mutation analysis at the surgical margin, 7 had undetectable TERT mutation, of which 5 also had a GTR (RV < 1cc). In these 5 patients at 30 months follow-up, 75% showed no progression, compared to 0% in the group with TERT mutations detected at the surgical margin (P = .02).

Conclusions: These findings identify a subset of patients with GBM that may derive local control benefits from radical resection to undetectable molecular margins.

Keywords: GBM; TERT promoter; extent of resection; postoperative survival; supramaximal resection.

Figure 1.

Survival benefits of residual volume (RV) < 4.9cc. (A) Kaplan–Meier curve of Progression-Free Survival (PFS) curves in patients with RV > 4.9cc vs RV < 4.9cc. (B) Kaplan–Meier curve of Overall Survival (OS) in patients with RV > 4.9cc vs RV < 4.9cc.

Figure 2.

Diagram demonstrating the workflow for processing data in the retrospective dataset. One hundred and forty-eight patients with IDH-WT GBM who underwent maximally safe resection underwent volumetric analysis of their pre-op and post-op scan (A) with subsequent tumor segmentation and volume measurement in Visage Imaging. Overall trend of residual volume as a function of pre-op tumor volume is shown on the scatter plot. Simultaneously tissue samples were analyzed with SnaPshot Genotyping assay consisting of multiplex PCR, single-base extension sequencing reaction with fluorescent dideoxynucleotide labeling allowing for mutant and wild-type allele detection (B). Frequency of genetic alterations in 3 critical signaling pathways (PI3K/MAPK, p53, and RB) from the SnaPshot assay are shown in C. Red is used to indicate activating genetic alterations and blue indicates inactivating mutations. Frequency of mutations are both listed numerically as a percentage of the total 148 patients and is shown visually by intensity of color.

Figure 3.

The association of molecular alterations with residual volume (RV) following maximal safe resection. (A) The 15 genes most frequently altered in the SnaPshot analysis with the frequency of each gene shown (right). Each column represents a patient organized by descending RV (bottom). (B) Correlation of 11 genomic alterations with RV, with amplifications of PDGFRA, KIT, KDR, and MDM4 on Chr4q12 being significantly correlated with higher RV. (C, D) Relationship between mutation allele frequency (MAF) of tumor suppressor genes and RV. A significant positive correlation between TP53 MAF and RV (C, P = .04) and between RB1 MAF and RV was observed (D, P = .02).

Figure 4.

Validation of model predicting the extent of resection. (A) Results from predictive model algorithm ranking the importance of surgical, radiographic, and molecular features in predicting a resection with RV < 4.9. (B) ML algorithm area under the curve analysis utilizing Surgical adjuncts (S) and Radiographic Features (R) for the testing and training sets including and excluding Molecular Features (M).

Figure 5.

Variation in clinical outcomes of patients with gross-total resection. Clinical course of 2 patients with GBM who underwent safe maximal resection. Patient 1 had a TERT C250T mutant GBM had undetectable TERT in the margin while patient 2 with TERT C228T mutant GBM had detectable TERT at the surgical margin. The overall clinical course with regard to tumor progression is displayed in the timeline.

Figure 6.

Progression-free survival and overall survival of patients stratified by resection and tumor contact at surgical margin. (A) Kaplan–Meier of progression-free survival in prospective cohort following Subtotal Resection (STR, green), gross-total resection (GTR) with TERTp positive margin (GTR + TERTp positive margin, blue), and GTR with TERTp negative margin (GTR + TERTp negative margin, red). (B) Kaplan–Meier curve of overall survival in prospective cohort grouped by STR, GTR + TERTp positive margin, and GTR + TERTp negative margin.