Glioma progression is shaped by genetic evolution and microenvironment interactions.

The factors driving therapy resistance in diffuse glioma remain poorly understood. To identify treatment-associated cellular and genetic changes, we analyzed RNA and/or DNA sequencing data from the temporally separated tumor pairs of 304 adult patients with isocitrate dehydrogenase (IDH)-wild-type and IDH-mutant glioma. Tumors recurred in distinct manners that were dependent on IDH mutation status and attributable to changes in histological feature composition, somatic alterations, and microenvironment interactions. Hypermutation and acquired CDKN2A deletions were associated with an increase in proliferating neoplastic cells at recurrence in both glioma subtypes, reflecting active tumor growth. IDH-wild-type tumors were more invasive at recurrence, and their neoplastic cells exhibited increased expression of neuronal signaling programs that reflected a possible role for neuronal interactions in promoting glioma progression. Mesenchymal transition was associated with the presence of a myeloid cell state defined by specific ligand-receptor interactions with neoplastic cells. Collectively, these recurrence-associated phenotypes represent potential targets to alter disease progression.

A Patient-Derived Glioblastoma Organoid Model and Biobank Recapitulates Inter- and Intra-tumoral Heterogeneity.

Glioblastomas exhibit vast inter- and intra-tumoral heterogeneity, complicating the development of effective therapeutic strategies. Current in vitro models are limited in preserving the cellular and mutational diversity of parental tumors and require a prolonged generation time. Here, we report methods for generating and biobanking patient-derived glioblastoma organoids (GBOs) that recapitulate the histological features, cellular diversity, gene expression, and mutational profiles of their corresponding parental tumors. GBOs can be generated quickly with high reliability and exhibit rapid, aggressive infiltration when transplanted into adult rodent brains. We further demonstrate the utility of GBOs to test personalized therapies by correlating GBO mutational profiles with responses to specific drugs and by modeling chimeric antigen receptor T cell immunotherapy. Our studies show that GBOs maintain many key features of glioblastomas and can be rapidly deployed to investigate patient-specific treatment strategies. Additionally, our live biobank establishes a rich resource for basic and translational glioblastoma research.

Direct enzymatic sequencing of 5-methylcytosine at single-base resolution.

5-methylcytosine (5mC) is the most important DNA modification in mammalian genomes. The ideal method for 5mC localization would be both nondestructive of DNA and direct, without requiring inference based on detection of unmodified cytosines. Here we present direct methylation sequencing (DM-Seq), a bisulfite-free method for profiling 5mC at single-base resolution using nanogram quantities of DNA. DM-Seq employs two key DNA-modifying enzymes: a neomorphic DNA methyltransferase and a DNA deaminase capable of precise discrimination between cytosine modification states. Coupling these activities with deaminase-resistant adapters enables accurate detection of only 5mC via a C-to-T transition in sequencing. By comparison, we uncover a PCR-related underdetection bias with the hybrid enzymatic-chemical TET-assisted pyridine borane sequencing approach. Importantly, we show that DM-Seq, unlike bisulfite sequencing, unmasks prognostically important CpGs in a clinical tumor sample by not confounding 5mC with 5-hydroxymethylcytosine. DM-Seq thus offers an all-enzymatic, nondestructive, faithful and direct method for the reading of 5mC alone.

ROS1 Alterations as a Potential Driver of Gliomas in Infant, Pediatric, and Adult Patients.

Gliomas harboring oncogenic ROS1 alterations are uncommon and primarily described in infants. Our goal was to characterize the clinicopathological features and molecular signatures of the full spectrum of ROS1 fusion-positive gliomas across all age groups. Through a retrospective multi-institutional collaboration, we report a collection of unpublished ROS1 fusion gliomas along with the characterization and meta-analysis of new and published cases. A cohort of 32 new and 58 published cases was divided into the following 3 age groups: 19 infants, 40 pediatric patients, and 31 adults with gliomas. Tumors in infants and adults showed uniformly high-grade morphology; however, tumors in pediatric patients exhibited diverse histologic features. The GOPC::ROS1 fusion was prevalent (61/79, 77%) across all age groups, and 10 other partner genes were identified. Adult tumors showed recurrent genomic alterations characteristic of IDH wild-type glioblastoma, including the +7/-10/CDKN2A deletion; amplification of CDK4, MDM2, and PDGFRA genes; and mutations involving TERTp, TP53, PIK3R1, PIK3CA, PTEN, and NF1 genes. Infant tumors showed few genomic alterations, whereas pediatric tumors showed moderate genomic complexity. The outcomes were significantly poorer in adult patients. Although not statistically significant, tumors in infant and pediatric patients with high-grade histology and in hemispheric locations appeared more aggressive than tumors with lower grade histology or those in nonhemispheric locations. In conclusion, this study is the largest to date to characterize the clinicopathological and molecular signatures of ROS1 fusion-positive gliomas from infant, pediatric, and adult patients. We conclude that ROS1 likely acts as a driver in infant and pediatric gliomas and as a driver or codriver in adult gliomas. Integrated comprehensive clinical testing might be helpful in identifying such patients for possible targeted therapy.

Validation of multiparametric MRI based prediction model in identification of pseudoprogression in glioblastomas.

BACKGROUND: Accurate differentiation of pseudoprogression (PsP) from tumor progression (TP) in glioblastomas (GBMs) is essential for appropriate clinical management and prognostication of these patients. In the present study, we sought to validate the findings of our previously developed multiparametric MRI model in a new cohort of GBM patients treated with standard therapy in identifying PsP cases. METHODS: Fifty-six GBM patients demonstrating enhancing lesions within 6 months after completion of concurrent chemo-radiotherapy (CCRT) underwent anatomical imaging, diffusion and perfusion MRI on a 3 T magnet. Subsequently, patients were classified as TP + mixed tumor (n = 37) and PsP (n = 19). When tumor specimens were available from repeat surgery, histopathologic findings were used to identify TP + mixed tumor (> 25% malignant features; n = 34) or PsP (< 25% malignant features; n = 16). In case of non-availability of tumor specimens, ≥ 2 consecutive conventional MRIs using mRANO criteria were used to determine TP + mixed tumor (n = 3) or PsP (n = 3). The multiparametric MRI-based prediction model consisted of predictive probabilities (PP) of tumor progression computed from diffusion and perfusion MRI derived parameters from contrast enhancing regions. In the next step, PP values were used to characterize each lesion as PsP or TP+ mixed tumor. The lesions were considered as PsP if the PP value was < 50% and TP+ mixed tumor if the PP value was ≥ 50%. Pearson test was used to determine the concordance correlation coefficient between PP values and histopathology/mRANO criteria. The area under ROC curve (AUC) was used as a quantitative measure for assessing the discriminatory accuracy of the prediction model in identifying PsP and TP+ mixed tumor. RESULTS: Multiparametric MRI model correctly predicted PsP in 95% (18/19) and TP+ mixed tumor in 57% of cases (21/37) with an overall concordance rate of 70% (39/56) with final diagnosis as determined by histopathology/mRANO criteria. There was a significant concordant correlation coefficient between PP values and histopathology/mRANO criteria (r = 0.56; p < 0.001). The ROC analyses revealed an accuracy of 75.7% in distinguishing PsP from TP+ mixed tumor. Leave-one-out cross-validation test revealed that 73.2% of cases were correctly classified as PsP and TP + mixed tumor. CONCLUSIONS: Our multiparametric MRI based prediction model may be helpful in identifying PsP in GBM patients.

Expanded analysis of high-grade astrocytoma with piloid features identifies an epigenetically and clinically distinct subtype associated with neurofibromatosis type 1.

High-grade astrocytoma with piloid features (HGAP) is a recently recognized glioma type whose classification is dependent on its global epigenetic signature. HGAP is characterized by alterations in the mitogen-activated protein kinase (MAPK) pathway, often co-occurring with CDKN2A/B homozygous deletion and/or ATRX mutation. Experience with HGAP is limited and to better understand this tumor type, we evaluated an expanded cohort of patients (n = 144) with these tumors, as defined by DNA methylation array testing, with a subset additionally evaluated by next-generation sequencing (NGS). Among evaluable cases, we confirmed the high prevalence CDKN2A/B homozygous deletion, and/or ATRX mutations/loss in this tumor type, along with a subset showing NF1 alterations. Five of 93 (5.4%) cases sequenced harbored TP53 mutations and RNA fusion analysis identified a single tumor containing an NTRK2 gene fusion, neither of which have been previously reported in HGAP. Clustering analysis revealed the presence of three distinct HGAP subtypes (or groups = g) based on whole-genome DNA methylation patterns, which we provisionally designated as gNF1 (n = 18), g1 (n = 72), and g2 (n = 54) (median ages 43.5 years, 47 years, and 32 years, respectively). Subtype gNF1 is notable for enrichment with patients with Neurofibromatosis Type 1 (33.3%, p = 0.0008), confinement to the posterior fossa, hypermethylation in the NF1 enhancer region, a trend towards decreased progression-free survival (p = 0.0579), RNA processing pathway dysregulation, and elevated non-neoplastic glia and neuron cell content (p < 0.0001 and p < 0.0001, respectively). Overall, our expanded cohort broadens the genetic, epigenetic, and clinical phenotype of HGAP and provides evidence for distinct epigenetic subtypes in this tumor type.

Molecular classification and grading of meningioma.

PURPOSE: Meningiomas are the most common primary intracranial tumor in older adults (Ostrom et al. in Neuro Oncol 21(Suppl 5):v1-v100, 2019). Treatment is largely driven by, in addition to patient characteristics and extent of resection/Simpson grade, the World Health Organization (WHO) grading of meningiomas. The current grading scheme, based predominantly on histologic features and only limited molecular characterization of these tumors (WHO Classification of Tumours Editorial Board, in: Central nervous system tumours, International Agency for Research on Cancer, Lyon, 2021), (Mirian et al. in J Neurol Neurosurg Psychiatry 91(4):379-387, 2020), does not consistently reflect the biologic behavior of meningiomas. This leads to both under-treatment and over-treatment of patients, and hence, suboptimal outcomes (Rogers et al. in Neuro Oncol 18(4):565-574). The goal of this review is to synthesize studies to date investigating molecular features of meningiomas as they relate to patient outcomes, in order to clarify best practices in assessing and, therefore, treating meningiomas. METHODS: The available literature of genomic landscape and molecular features of in meningioma was screened using PubMed. RESULTS: Greater understanding of meningiomas is reached by integrating histopathology, mutational analysis, DNA copy number changes, DNA methylation profiles, and potentially additional modalities to fully capture the clinical and biologic heterogeneity of these tumors. CONCLUSION: Diagnosis and classification of meningioma is best accomplished using a combination of histopathology with genomic and epigenomic factors. Future classification schemes may benefit from such an integrated approach.

Assessment of treatment response to dendritic cell vaccine in patients with glioblastoma using a multiparametric MRI-based prediction model.

PURPOSE: Autologous tumor lysate-loaded dendritic cell vaccine (DCVax-L) is a promising treatment modality for glioblastomas. The purpose of this study was to investigate the potential utility of multiparametric MRI-based prediction model in evaluating treatment response in glioblastoma patients treated with DCVax-L. METHODS: Seventeen glioblastoma patients treated with standard-of-care therapy + DCVax-L were included. When tumor progression (TP) was suspected and repeat surgery was being contemplated, we sought to ascertain the number of cases correctly classified as TP + mixed response or pseudoprogression (PsP) from multiparametric MRI-based prediction model using histopathology/mRANO criteria as ground truth. Multiparametric MRI model consisted of predictive probabilities (PP) of tumor progression computed from diffusion and perfusion MRI-derived parameters. A comparison of overall survival (OS) was performed between patients treated with standard-of-care therapy + DCVax-L and standard-of-care therapy alone (external controls). Additionally, Kaplan-Meier analyses were performed to compare OS between two groups of patients using PsP, Ki-67, and MGMT promoter methylation status as stratification variables. RESULTS: Multiparametric MRI model correctly predicted TP + mixed response in 72.7% of cases (8/11) and PsP in 83.3% (5/6) with an overall concordance rate of 76.5% with final diagnosis as determined by histopathology/mRANO criteria. There was a significant concordant correlation coefficient between PP values and histopathology/mRANO criteria (r = 0.54; p = 0.026). DCVax-L-treated patients had significantly prolonged OS than those treated with standard-of-care therapy (22.38 ± 12.8 vs. 13.8 ± 9.5 months, p = 0.040). Additionally, glioblastomas with PsP, MGMT promoter methylation status, and Ki-67 values below median had longer OS than their counterparts. CONCLUSION: Multiparametric MRI-based prediction model can assess treatment response to DCVax-L in patients with glioblastoma.

Association of partial T2-FLAIR mismatch sign and isocitrate dehydrogenase mutation in WHO grade 4 gliomas: results from the ReSPOND consortium.

PURPOSE: While the T2-FLAIR mismatch sign is highly specific for isocitrate dehydrogenase (IDH)-mutant, 1p/19q-noncodeleted astrocytomas among lower-grade gliomas, its utility in WHO grade 4 gliomas is not well-studied. We derived the partial T2-FLAIR mismatch sign as an imaging biomarker for IDH mutation in WHO grade 4 gliomas. METHODS: Preoperative MRI scans of adult WHO grade 4 glioma patients (n = 2165) from the multi-institutional ReSPOND (Radiomics Signatures for PrecisiON Diagnostics) consortium were analyzed. Diagnostic performance of the partial T2-FLAIR mismatch sign was evaluated. Subset analyses were performed to assess associations of imaging markers with overall survival (OS). RESULTS: One hundred twenty-one (5.6%) of 2165 grade 4 gliomas were IDH-mutant. Partial T2-FLAIR mismatch was present in 40 (1.8%) cases, 32 of which were IDH-mutant, yielding 26.4% sensitivity, 99.6% specificity, 80.0% positive predictive value, and 95.8% negative predictive value. Multivariate logistic regression demonstrated IDH mutation was significantly associated with partial T2-FLAIR mismatch (odds ratio [OR] 5.715, 95% CI [1.896, 17.221], p = 0.002), younger age (OR 0.911 [0.895, 0.927], p < 0.001), tumor centered in frontal lobe (OR 3.842, [2.361, 6.251], p < 0.001), absence of multicentricity (OR 0.173, [0.049, 0.612], p = 0.007), and presence of cystic (OR 6.596, [3.023, 14.391], p < 0.001) or non-enhancing solid components (OR 6.069, [3.371, 10.928], p < 0.001). Multivariate Cox analysis demonstrated cystic components (p = 0.024) and non-enhancing solid components (p = 0.003) were associated with longer OS, while older age (p < 0.001), frontal lobe center (p = 0.008), multifocality (p < 0.001), and multicentricity (p < 0.001) were associated with shorter OS. CONCLUSION: Partial T2-FLAIR mismatch sign is highly specific for IDH mutation in WHO grade 4 gliomas.

Locally secreted BiTEs complement CAR T cells by enhancing killing of antigen heterogeneous solid tumors.

Bispecific T cell engagers (BiTEs) are bispecific antibodies that redirect T cells to target antigen-expressing tumors. We hypothesized that BiTE-secreting T cells could be a valuable therapy in solid tumors, with distinct properties in mono- or multi-valent strategies incorporating chimeric antigen receptor (CAR) T cells. Glioblastomas represent a good model for solid tumor heterogeneity, representing a significant therapeutic challenge. We detected expression of tumor-associated epidermal growth factor receptor (EGFR), EGFR variant III, and interleukin-13 receptor alpha 2 (IL13Rα2) on glioma tissues and cancer stem cells. These antigens formed the basis of a multivalent approach, using a conformation-specific tumor-related EGFR targeting antibody (806) and Hu08, an IL13Rα2-targeting antibody, as the single chain variable fragments to generate new BiTE molecules. Compared with CAR T cells, BiTE T cells demonstrated prominent activation, cytokine production, and cytotoxicity in response to target-positive gliomas. Superior response activity was also demonstrated in BiTE-secreting bivalent T cells compared with bivalent CAR T cells in a glioma mouse model at early phase, but not in the long term. In summary, BiTEs secreted by mono- or multi-valent T cells have potent anti-tumor activity in vitro and in vivo with significant sensitivity and specificity, demonstrating a promising strategy in solid tumor therapy.

MR susceptibility imaging for detection of tumor-associated macrophages in glioblastoma.

PURPOSE: Tumor-associated macrophages (TAMs) are a key component of glioblastoma (GBM) microenvironment. Considering the differential role of different TAM phenotypes in iron metabolism with the M1 phenotype storing intracellular iron, and M2 phenotype releasing iron in the tumor microenvironment, we investigated MRI to quantify iron as an imaging biomarker for TAMs in GBM patients. METHODS: 21 adult patients with GBM underwent a 3D single echo gradient echo MRI sequence and quantitative susceptibility maps were generated. In 3 subjects, ex vivo imaging of surgical specimens was performed on a 9.4 Tesla MRI using 3D multi-echo GRE scans, and R2* (1/T2*) maps were generated. Each specimen was stained with hematoxylin and eosin, as well as CD68, CD86, CD206, and L-Ferritin. RESULTS: Significant positive correlation was observed between mean susceptibility for the tumor enhancing zone and the L-ferritin positivity percent (r = 0.56, p = 0.018) and the combination of tumor's enhancing zone and necrotic core and the L-Ferritin positivity percent (r = 0.72; p = 0.001). The mean susceptibility significantly correlated with positivity percent for CD68 (ρ = 0.52, p = 0.034) and CD86 (r = 0.7 p = 0.001), but not for CD206 (ρ = 0.09; p = 0.7). There was a positive correlation between mean R2* values and CD68 positive cell counts (r = 0.6, p = 0.016). Similarly, mean R2* values significantly correlated with CD86 (r = 0.54, p = 0.03) but not with CD206 (r = 0.15, p = 0.5). CONCLUSIONS: This study demonstrated the potential of MR quantitative susceptibility mapping as a non-invasive method for in vivo TAM quantification and phenotyping. Validation of these findings with large multicenter studies is needed.

Histopathology-validated machine learning radiographic biomarker for noninvasive discrimination between true progression and pseudo-progression in glioblastoma.

BACKGROUND: Imaging of glioblastoma patients after maximal safe resection and chemoradiation commonly demonstrates new enhancements that raise concerns about tumor progression. However, in 30% to 50% of patients, these enhancements primarily represent the effects of treatment, or pseudo-progression (PsP). We hypothesize that quantitative machine learning analysis of clinically acquired multiparametric magnetic resonance imaging (mpMRI) can identify subvisual imaging characteristics to provide robust, noninvasive imaging signatures that can distinguish true progression (TP) from PsP. METHODS: We evaluated independent discovery (n = 40) and replication (n = 23) cohorts of glioblastoma patients who underwent second resection due to progressive radiographic changes suspicious for recurrence. Deep learning and conventional feature extraction methods were used to extract quantitative characteristics from the mpMRI scans. Multivariate analysis of these features revealed radiophenotypic signatures distinguishing among TP, PsP, and mixed response that compared with similar categories blindly defined by board-certified neuropathologists. Additionally, interinstitutional validation was performed on 20 new patients. RESULTS: Patients who demonstrate TP on neuropathology are significantly different (P < .0001) from those with PsP, showing imaging features reflecting higher angiogenesis, higher cellularity, and lower water concentration. The accuracy of the proposed signature in leave-one-out cross-validation was 87% for predicting PsP (area under the curve [AUC], 0.92) and 84% for predicting TP (AUC, 0.83), whereas in the discovery/replication cohort, the accuracy was 87% for predicting PsP (AUC, 0.84) and 78% for TP (AUC, 0.80). The accuracy in the interinstitutional cohort was 75% (AUC, 0.80). CONCLUSION: Quantitative mpMRI analysis via machine learning reveals distinctive noninvasive signatures of TP versus PsP after treatment of glioblastoma. Integration of the proposed method into clinical studies can be performed using the freely available Cancer Imaging Phenomics Toolkit.

Multiparametric magnetic resonance imaging in the assessment of anti-EGFRvIII chimeric antigen receptor T cell therapy in patients with recurrent glioblastoma.

EGFRvIII targeted chimeric antigen receptor T (CAR-T) cell therapy has recently been reported for treating glioblastomas (GBMs); however, physiology-based MRI parameters have not been evaluated in this setting. Ten patients underwent multiparametric MRI at baseline, 1, 2 and 3 months after CAR-T therapy. Logistic regression model derived progression probabilities (PP) using imaging parameters were used to assess treatment response. Four lesions from "early surgery" group demonstrated high PP at baseline suggestive of progression, which was confirmed histologically. Out of eight lesions from remaining six patients, three lesions with low PP at baseline remained stable. Two lesions with high PP at baseline were associated with large decreases in PP reflecting treatment response, whereas other two lesions with high PP at baseline continued to demonstrate progression. One patient didn't have baseline data but demonstrated progression on follow-up. Our findings indicate that multiparametric MRI may be helpful in monitoring CAR-T related early therapeutic changes in GBM patients.

Histone H3K27 dimethyl loss is highly specific for malignant peripheral nerve sheath tumor and distinguishes true PRC2 loss from isolated H3K27 trimethyl loss.

Malignant peripheral nerve sheath tumors contain loss of histone H3K27 trimethylation (H3K27me3) due to driver mutations affecting the polycomb repressive complex 2 (PRC2). Consequently, loss of H3K27me3 staining has served as a diagnostic marker for this tumor type. However, recent reports demonstrate H3K27me3 loss in numerous other tumors, including some in the differential diagnosis of malignant peripheral nerve sheath tumor. Since these tumors lose H3K27me3 through mechanisms distinct from PRC2 loss, we set out to determine whether loss of dimethylation of H3K27, which is also catalyzed by PRC2, might be a more specific marker of PRC2 loss and malignant peripheral nerve sheath tumor. Using mass spectrometry, we identify a near complete loss of H3K27me2 in malignant peripheral nerve sheath tumors and cell lines. Immunohistochemical analysis of 72 malignant peripheral nerve sheath tumors, seven K27M-mutant gliomas, 43 ependymomas, and 10 Merkel cell carcinomas demonstrates that while H3K27me3 loss is common across these tumor types, H3K27me2 loss is limited to malignant peripheral nerve sheath tumors and is highly concordant with H3K27me3 loss (33/34 cases). Thus, increased specificity does not come at the cost of greatly reduced sensitivity. To further compare H3K27me2 and H3K27me3 immunohistochemistry, we investigated 42 melanomas and 54 synovial sarcomas, histologic mimics of malignant peripheral nerve sheath tumor with varying degrees of H3K27me3 loss in prior reports. While global H3K27me3 loss was not seen in these tumors, weak and limited H3K27me3 staining was common. By contrast, H3K27me2 staining was more clearly retained in all cases, making it a superior binary classifier. This was confirmed by digital image analysis of stained slides. Our findings indicate that H3K27me2 loss is highly specific for PRC2 loss and that PRC2 loss is a rarer phenomenon than H3K27me3 loss. Consequently, H3K27me2 loss is a superior diagnostic marker for malignant peripheral nerve sheath tumor.

Three-dimensional echo planar spectroscopic imaging for differentiation of true progression from pseudoprogression in patients with glioblastoma.

Accurate differentiation of true progression (TP) from pseudoprogression (PsP) in patients with glioblastomas (GBMs) is essential for planning adequate treatment and for estimating clinical outcome measures and future prognosis. The purpose of this study was to investigate the utility of three-dimensional echo planar spectroscopic imaging (3D-EPSI) in distinguishing TP from PsP in GBM patients. For this institutional review board approved and HIPAA compliant retrospective study, 27 patients with GBM demonstrating enhancing lesions within six months of completion of concurrent chemo-radiation therapy were included. Of these, 18 were subsequently classified as TP and 9 as PsP based on histological features or follow-up MRI studies. Parametric maps of choline/creatine (Cho/Cr) and choline/N-acetylaspartate (Cho/NAA) were computed and co-registered with post-contrast T1 -weighted and FLAIR images. All lesions were segmented into contrast enhancing (CER), immediate peritumoral (IPR), and distal peritumoral (DPR) regions. For each region, Cho/Cr and Cho/NAA ratios were normalized to corresponding metabolite ratios from contralateral normal parenchyma and compared between TP and PsP groups. Logistic regression analyses were performed to obtain the best model to distinguish TP from PsP. Significantly higher Cho/NAA was observed from CER (2.69 ± 1.00 versus 1.56 ± 0.51, p = 0.003), IPR (2.31 ± 0.92 versus 1.53 ± 0.56, p = 0.030), and DPR (1.80 ± 0.68 versus 1.19 ± 0.28, p = 0.035) regions in TP patients compared with those with PsP. Additionally, significantly elevated Cho/Cr (1.74 ± 0.44 versus 1.34 ± 0.26, p = 0.023) from CER was observed in TP compared with PsP. When these parameters were incorporated in multivariate regression analyses, a discriminatory model with a sensitivity of 94% and a specificity of 87% was observed in distinguishing TP from PsP. These results indicate the utility of 3D-EPSI in differentiating TP from PsP with high sensitivity and specificity.

Differentiation of brain infection from necrotic glioblastoma using combined analysis of diffusion and perfusion MRI.

BACKGROUND: Accurate differentiation of brain infections from necrotic glioblastomas (GBMs) may not always be possible on morphologic MRI or on diffusion tensor imaging (DTI) and dynamic susceptibility contrast perfusion-weighted imaging (DSC-PWI) if these techniques are used independently. PURPOSE: To investigate the combined analysis of DTI and DSC-PWI in distinguishing brain injections from necrotic GBMs. STUDY TYPE: Retrospective. POPULATION: Fourteen patients with brain infections and 21 patients with necrotic GBMs. FIELD STRENGTH/SEQUENCE: 3T MRI, DTI, and DSC-PWI. ASSESSMENT: Parametric maps of mean diffusivity (MD), fractional anisotropy (FA), coefficient of linear (CL), and planar anisotropy (CP) and leakage corrected cerebral blood volume (CBV) were computed and coregistered with postcontrast T1 -weighted and FLAIR images. All lesions were segmented into the central core and enhancing region. For each region, median values of MD, FA, CL, CP, relative CBV (rCBV), and top 90th percentile of rCBV (rCBVmax ) were measured. STATISTICAL TESTS: All parameters from both regions were compared between brain infections and necrotic GBMs using Mann-Whitney tests. Logistic regression analyses were performed to obtain the best model in distinguishing these two conditions. RESULTS: From the central core, significantly lower MD (0.90 × 10-3 ± 0.44 × 10-3 mm2 /s vs. 1.66 × 10-3 ± 0.62 × 10-3 mm2 /s, P = 0.001), significantly higher FA (0.15 ± 0.06 vs. 0.09 ± 0.03, P < 0.001), and CP (0.07 ± 0.03 vs. 0.04 ± 0.02, P = 0.009) were observed in brain infections compared to those in necrotic GBMs. Additionally, from the contrast-enhancing region, significantly lower rCBV (1.91 ± 0.95 vs. 2.76 ± 1.24, P = 0.031) and rCBVmax (3.46 ± 1.41 vs. 5.89 ± 2.06, P = 0.001) were observed from infective lesions compared to necrotic GBMs. FA from the central core and rCBVmax from enhancing region provided the best classification model in distinguishing brain infections from necrotic GBMs, with a sensitivity of 91% and a specificity of 93%. DATA CONCLUSION: Combined analysis of DTI and DSC-PWI may provide better performance in differentiating brain infections from necrotic GBMs. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:184-194.

Histopathologic quantification of viable tumor versus treatment effect in surgically resected recurrent glioblastoma.

PURPOSE: The prognostic impact of the histopathologic features of recurrent glioblastoma surgical specimens is unknown. We sought to determine whether key histopathologic characteristics in glioblastoma tumors resected after chemoradiotherapy are associated with overall survival (OS). METHODS: The following characteristics were quantified in recurrent glioblastoma specimens at our institution: extent of viable tumor (accounting for % of specimen comprised of tumor and tumor cellularity), mitoses per 10 high-power fields (0, 1-10, > 10), Ki-67 proliferative index (0-100%), hyalinization (0-6; none to extensive), rarefaction (0-6), hemosiderin (0-6), and % of specimen comprised of geographic necrosis (0-100%; converted to 0-6 scale). Variables associated with OS in univariate analysis, as well as age, eastern cooperative oncology group performance status (ECOG PS), extent of repeat resection, time from initial diagnosis to repeat surgery, and O6-methylguanine-DNA methyltransferase promoter methylation, were included in a multivariable Cox proportional hazards model. RESULTS: 37 specimens were assessed. In a multivariate model, high Ki-67 proliferative index was the only histopathologic characteristic associated with worse OS following repeat surgery for glioblastoma (hazard ratio (HR) 1.3, 95% CI 1.1-1.5, p = 0.003). Shorter time interval from initial diagnosis to repeat surgery (HR 1.11, 95% CI 1.02-1.21, p = 0.016) and ECOG PS ≥ 2 (HR 4.19, 95% CI 1.72-10.21, p = 0.002) were also independently associated with inferior OS. CONCLUSION: In patients with glioblastoma undergoing repeat resection following chemoradiotherapy, high Ki-67 index in the recurrent specimen, short time to recurrence, and poor PS are independently associated with worse OS. Histopathologic quantification of viable tumor versus therapy-related changes has limited prognostic influence.

Negative prognostic impact of epidermal growth factor receptor copy number gain in young adults with isocitrate dehydrogenase wild-type glioblastoma.

PURPOSE: Young adults with isocitrate-dehydrogenase wild-type (IDH-WT) glioblastoma (GBM) represent a rare, understudied population compared to pediatric high-grade glioma, IDH-mutant GBM, or IDH-WT GBM in older patients. We aimed to explore the prognostic impact of epidermal growth factor receptor copy number gain (EGFR CN gain), one of the most common genetic alterations in IDH-WT glioma, in young adults with IDH-WT GBM. METHODS: We performed a retrospective cohort study of patients 18-45 years old with newly diagnosed, IDH-WT GBM whose tumors underwent next-generation sequencing at our institution between 2014 and 2018. The impact of EGFR CN gain on time to tumor progression (TTP) and overall survival (OS) was assessed. A validation cohort of patients 18-45 years old with IDH-WT GBM was analyzed from The Cancer Genome Atlas (TCGA). RESULTS: Ten of 28 patients (36%) from our institution had EGFR CN gain, which was associated with shorter TTP (median 6.5 vs. 11.9 months; p = 0.06) and OS (median 16.3 vs. 23.5 months; p = 0.047). The negative prognostic impact of EGFR CN gain on OS persisted in a multivariate model (HR 6.40, 95% CI 1.3-31.0, p = 0.02). In the TCGA cohort (N = 43), EGFR CN gain was associated with shorter TTP and worse OS, although these did not reach statistical significance (TTP, median 11.5 vs. 14.4 months, p = 0.18; OS, median 23.6 vs. 27.8 months; p = 0.18). CONCLUSIONS: EGFR CN gain may be associated with inferior outcomes in young adults with newly diagnosed, IDH-WT GBM, suggesting a potential role for targeting EGFR in this population.