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.

Magnetic resonance image features identify glioblastoma phenotypic subtypes with distinct molecular pathway activities.

Glioblastoma (GBM) is the most common and highly lethal primary malignant brain tumor in adults. There is a dire need for easily accessible, noninvasive biomarkers that can delineate underlying molecular activities and predict response to therapy. To this end, we sought to identify subtypes of GBM, differentiated solely by quantitative magnetic resonance (MR) imaging features, that could be used for better management of GBM patients. Quantitative image features capturing the shape, texture, and edge sharpness of each lesion were extracted from MR images of 121 single-institution patients with de novo, solitary, unilateral GBM. Three distinct phenotypic "clusters" emerged in the development cohort using consensus clustering with 10,000 iterations on these image features. These three clusters--pre-multifocal, spherical, and rim-enhancing, names reflecting their image features--were validated in an independent cohort consisting of 144 multi-institution patients with similar tumor characteristics from The Cancer Genome Atlas (TCGA). Each cluster mapped to a unique set of molecular signaling pathways using pathway activity estimates derived from the analysis of TCGA tumor copy number and gene expression data with the PARADIGM (Pathway Recognition Algorithm Using Data Integration on Genomic Models) algorithm. Distinct pathways, such as c-Kit and FOXA, were enriched in each cluster, indicating differential molecular activities as determined by the image features. Each cluster also demonstrated differential probabilities of survival, indicating prognostic importance. Our imaging method offers a noninvasive approach to stratify GBM patients and also provides unique sets of molecular signatures to inform targeted therapy and personalized treatment of GBM.

Hydrogen bond residue positioning in the 599-611 loop of thimet oligopeptidase is required for substrate selection.

Thimet oligopeptidase (EC 3.4.24.15) is a zinc(II) endopeptidase implicated in the processing of numerous physiological peptides. Although its role in selecting and processing peptides is not fully understood, it is believed that flexible loop regions lining the substrate-binding site allow the enzyme to conform to substrates of varying structure. This study describes mutant forms of thimet oligopeptidase in which Gly or Tyr residues in the 599-611 loop region were replaced, individually and in combination, to elucidate the mechanism of substrate selection by this enzyme. Decreases in k(cat) observed on mutation of Tyr605 and Tyr612 demonstrate that these residues contribute to the efficient cleavage of most substrates. Modeling studies showing that a hinge-bend movement brings both Tyr612 and Tyr605 within hydrogen bond distance of the cleaved peptide bond supports this role. Thus, molecular modeling studies support a key role in transition state stabilization of this enzyme by Tyr605. Interestingly, kinetic parameters show that a bradykinin derivative is processed distinctly from the other substrates tested, suggesting that an alternative catalytic mechanism may be employed for this particular substrate. The data demonstrate that neither Tyr605 nor Tyr612 is necessary for the hydrolysis of this substrate. Relative to other substrates, the bradykinin derivative is also unaffected by Gly mutations in the loop. This distinction suggests that the role of Gly residues in the loop is to properly orientate these Tyr residues in order to accommodate varying substrate structures. This also opens up the possibility that certain substrates may be cleaved by an open form of the enzyme.