Current Management of Adult Diffuse Infiltrative Low Grade Gliomas

T2-FLAIR imaging-based radiomic features for predicting early postoperative recurrence of grade II gliomas

Aim: To develop and validate a T2-weighted-fluid attenuated inversion recovery (T2-FLAIR) images-based radiomics model for predicting early postoperative recurrence (within 1 year) in patients with low-grade gliomas (LGGs).Methods: A retrospective analysis was performed by collecting clinical, pathological and magnetic resonance imaging (MRI) data from patients with LGG between 2017 and 2022. Regions of interest were delineated and radiomic features were extracted from T2-FLAIR images using 3D-Slicer software. To minimize redundant features, the Least Absolute Shrinkage and Selection Operator (LASSO) regression algorithm was used. Patients were categorized into two groups based on recurrence status: the recurrence group (RG) and the non-recurrence group (NRG). Radiomic features were used to develop models using three machine learning approaches: logistic regression (LR), random forest (RF) and support vector machine (SVM). The performance of the radiomic features was validated using fivefold cross-validation.Results: After rigorous screening, 105 patients met the inclusion criteria, and five radiomic features were identified. After 5-folds cross-validation, the average areas under the curves for LR, RF and SVM were 0.813, 0.741 and 0.772, respectively.Conclusion: T2-FLAIR-based radiomic features effectively predicted early recurrence in postoperative LGGs.

Predictors of tumor progression of low-grade glioma in adult patients within 5 years follow-up after surgery

Background

Glioma originates from glial cells in the brain and is the most common primary intracranial tumor. This study intends to use a retrospective analysis to explore the factors that can predict tumor progression in adult low-grade gliomas, namely WHO II grade patients, within 5 years after surgery.

Methods

Patients with WHO grade II glioma who were surgically treated in our hospital from February 2011 to May 2017 were included. According to the inclusion and exclusion criteria, 252 patients were included in the final analysis. According to the results of the 5-year follow-up (including survival and imaging review results), patients were divided into progression-free group and progression group. Univariate and multivariate analysis were conducted to investigate the related factors of tumor progression during the 5-year follow-up.

Results

The results of the 5-year follow-up showed that 111 (44.0%) cases had no progress (progression free group, PFG), 141 (56.0%) cases had progress (progression group, PG), of which 43 (30.5%) cases were operated again, 37 cases (26.2%) received non-surgical treatments. There were 26 (10.3%) all-cause deaths, and 21 (8.3%) tumor-related deaths. Univariate and multivariate analysis showed that age >45 years old (OR = 1.35, 95% CI, 1.07-3.19, P = 0.027), partial tumor resection (OR = 1.66, 95% CI, 1.15-3.64, P = 0.031), tumor diameter >3 cm (OR = 1.52, 95% CI, 1.14-4.06, P = 0.017) and no radiotherapy (OR = 1.37, 95% CI, 1.12-2.44, P = 0.039) were independent predictors of the progression of tumor during the 5-year follow-up period.

Conclusion

Age >45 years old, partial tumor resection, tumor diameter >3 cm, no radiotherapy are predictors for tumor progression for glioma patients after surgery.

Advanced Imaging Techniques for Newly Diagnosed and Recurrent Gliomas

Management of gliomas following initial diagnosis requires thoughtful presurgical planning followed by regular imaging to monitor treatment response and survey for new tumor growth. Traditional MR imaging modalities such as T1 post-contrast and T2-weighted sequences have long been a staple of tumor diagnosis, surgical planning, and post-treatment surveillance. While these sequences remain integral in the management of gliomas, advances in imaging techniques have allowed for a more detailed characterization of tumor characteristics. Advanced MR sequences such as perfusion, diffusion, and susceptibility weighted imaging, as well as PET scans have emerged as valuable tools to inform clinical decision making and provide a non-invasive way to help distinguish between tumor recurrence and pseudoprogression. Furthermore, these advances in imaging have extended to the operating room and assist in making surgical resections safer. Nevertheless, surgery, chemotherapy, and radiation treatment continue to make the interpretation of MR changes difficult for glioma patients. As analytics and machine learning techniques improve, radiomics offers the potential to be more quantitative and personalized in the interpretation of imaging data for gliomas. In this review, we describe the role of these newer imaging modalities during the different stages of management for patients with gliomas, focusing on the pre-operative, post-operative, and surveillance periods. Finally, we discuss radiomics as a means of promoting personalized patient care in the future.

Whole-Tumor Histogram Analysis of Multiple Diffusion Metrics for Glioma Genotyping

Background The isocitrate dehydrogenase (IDH) genotype and 1p/19q codeletion status are key molecular markers included in glioma pathologic diagnosis. Advanced diffusion models provide additional microstructural information. Purpose To compare the diagnostic performance of histogram features of multiple diffusion metrics in predicting glioma IDH and 1p/19q genotyping. Materials and Methods In this prospective study, participants were enrolled from December 2018 to December 2020. Diffusion-weighted imaging was performed by using a spin-echo echo-planar imaging sequence with five b values (500, 1000, 1500, 2000, and 2500 sec/mm²) in 30 directions for every b value and one b value of 0. Diffusion metrics of diffusion-tensor imaging (DTI), diffusion-kurtosis imaging (DKI), neurite orientation dispersion and density imaging (NODDI), and mean apparent propagator (MAP) were calculated, and their histogram features were analyzed in regions that included the entire tumor and peritumoral edema. Comparisons between groups were performed according to IDH genotype and 1p/19q codeletion status. Logistic regression analysis was used to predict the IDH and 1p/19q genotypes. Results A total of 215 participants (115 men, 100 women; mean age, 48 years ± 13 [standard deviation]) with grade II (n = 68), grade III (n = 35), and grade IV (n = 112) glioma were included. Among the DTI, DKI, NODDI, MAP, and total diffusion models, there were no significant differences in the areas under the receiver operating characteristic curve (AUCs) for predicting IDH mutations (AUC, 0.76, 0.82, 0.78, 0.81, and 0.82, respectively; P > .05) and 1p/19q codeletion in gliomas with IDH mutations (AUC, 0.83, 0.81, 0.82, 0.83, and 0.88, respectively; P > .05). A regression model with an R² value of 0.84 was used for the Ki-67 labeling index and histogram features of the diffusion metrics. Conclusion Whole-tumor histogram analysis of multiple diffusion metrics is a promising approach for glioma isocitrate dehydrogenase and 1p/19q genotyping, and the performance of diffusion-tensor imaging is similar to that of advanced diffusion models. Clinical trial registration no. ChiCTR2100048119 © RSNA, 2021 Online supplemental material is available for this article.

Do the combination of multiparametric MRI-based radiomics and selected blood inflammatory markers predict the grade and proliferation in glioma patients?

PURPOSE

We aimed to explore whether multiparametric magnetic resonance imaging (MRI)-based radiomics combined with selected blood inflammatory markers could effectively predict the grade and proliferation in glioma patients.

METHODS

This retrospective study included 152 patients histopathologically diagnosed with glioma. Stratified sampling was used to divide all patients into a training cohort (n=107) and a validation cohort (n=45) according to a ratio of 7:3, and five-fold repeat cross-validation was adopted in the training cohort. Multiparametric MRI and clinical parameters, including age, the neutrophil-lymphocyte ratio and red cell distribution width, were assessed. During image processing, image registration and gray normalization were conducted. A radiomics analysis was performed by extracting 1584 multiparametric MRI-based features, and the least absolute shrinkage and selection operator (LASSO) was applied to generate a radiomics signature for predicting grade and Ki-67 index in both training and validation cohorts. Statistical analysis included analysis of variance, Pearson correlation, intraclass correlation coefficient, multivariate logistic regression, Hosmer-Lemeshow test, and receiver operating characteristic (ROC) curve.

RESULTS

The radiomics signature demonstrated good performance in both the training and validation cohorts, with areas under the ROC curve (AUCs) of 0.92, 0.91, and 0.94 and 0.94, 0.75, and 0.82 for differentiating between low and high grade gliomas, grade III and grade IV gliomas, and low Ki-67 and high Ki-67, respectively, and was better than the clinical model; the AUCs of the combined model were 0.93, 0.91, and 0.95 and 0.94, 0.76, and 0.80, respectively.

CONCLUSION

Both the radiomics signature and combined model showed high diagnostic efficacy and outperformed the clinical model. The clinical factors did not provide additional improvement in the prediction of the grade and proliferation index in glioma patients, but the stability was improved.

Dysregulated Expression and Methylation Analysis Identified TLX1NB as a Novel Recurrence Marker in Low-Grade Gliomas

Low-grade gliomas (LGGs) are the most common CNS tumors, and the main therapy for LGGs is complete surgical resection, due to its curative effect. However, LGG recurrence occurs frequently. Biomarkers play a crucial role in evaluating the recurrence and prognosis of LGGs. Numerous studies have focused on LGG prognosis. However, the multiomics research investigating the roles played by gene methylation and expression in LGG recurrence remains limited. In this study, we integrated the TCGA and GEO datasets, analyzing RNA and methylation data for recurrence (R) and nonrecurrence (NR) groups. We found a low expression of TLX1NB and high methylation in recurrence patients. Low expression of TLX1NB is associated with poor survival (OS: p = 0.04). The expression of TLX1NB is likely to play a role in the prognosis of LGG. Therefore, TLX1NB may represent an alternative early biomarker for the recurrence of low-grade gliomas.

Early versus delayed postoperative radiotherapy for treatment of low-grade gliomas

BACKGROUND

This is an update of the review originally published in 2011 and first updated in 2015. In most people with low-grade gliomas (LGG), the primary treatment regimen remains a combination of surgery followed by postoperative radiotherapy. However, the optimal timing of radiotherapy is controversial. It is unclear whether to use radiotherapy in the early postoperative period, or whether radiotherapy should be delayed until tumour progression occurs.

OBJECTIVES

To assess the effects of early postoperative radiotherapy versus radiotherapy delayed until tumour progression for low-grade intracranial gliomas in people who had initial biopsy or surgical resection.

SEARCH METHODS

Original searches were run up to September 2014. An updated literature search from September 2014 through November 2019 was performed on the following electronic databases: the Cochrane Central Register of Controlled Trials (CENTRAL; 2019, Issue 11), MEDLINE via Ovid (September 2014 to November week 2 2019), and Embase via Ovid (September 2014 to 2019 week 46) to identify trials for inclusion in this Cochrane review update.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) that compared early versus delayed radiotherapy following biopsy or surgical resection for the treatment of people with newly diagnosed intracranial LGG (astrocytoma, oligodendroglioma, mixed oligoastrocytoma, astroblastoma, xanthoastrocytoma, or ganglioglioma). Radiotherapy may include conformal external beam radiotherapy (EBRT) with linear accelerator or cobalt-60 sources, intensity-modulated radiotherapy (IMRT), or stereotactic radiosurgery (SRS).

DATA COLLECTION AND ANALYSIS

Three review authors independently assessed the trials for inclusion and risk of bias, and extracted study data. We resolved any differences between review authors by discussion. Adverse effects were also extracted from the study report. We performed meta-analyses using a random-effects model with inverse variance weighting.

MAIN RESULTS

We included one large, multi-institutional, prospective RCT, involving 311 participants; the risk of bias in this study was unclear. This study found that early postoperative radiotherapy was associated with an increase in time to progression compared to observation (and delayed radiotherapy upon disease progression) for people with LGG but did not significantly improve overall survival (OS). The median progression-free survival (PFS) was 5.3 years in the early radiotherapy group and 3.4 years in the delayed radiotherapy group (hazard ratio (HR) 0.59, 95% confidence interval (CI) 0.45 to 0.77; P < 0.0001; 311 participants; 1 trial; low-quality evidence). The median OS in the early radiotherapy group was 7.4 years, while the delayed radiotherapy group experienced a median overall survival of 7.2 years (HR 0.97, 95% CI 0.71 to 1.33; P = 0.872; 311 participants; 1 trial; low-quality evidence). The total dose of radiotherapy given was 54 Gy; five fractions of 1.8 Gy per week were given for six weeks. Adverse effects following radiotherapy consisted of skin reactions, otitis media, mild headache, nausea, and vomiting. Rescue therapy was provided to 65% of the participants randomised to delayed radiotherapy. People in both cohorts who were free from tumour progression showed no differences in cognitive deficit, focal deficit, performance status, and headache after one year. However, participants randomised to the early radiotherapy group experienced significantly fewer seizures than participants in the delayed postoperative radiotherapy group at one year (25% versus 41%, P = 0.0329, respectively).

AUTHORS' CONCLUSIONS

Given the high risk of bias in the included study, the results of this analysis must be interpreted with caution. Early radiation therapy was associated with the following adverse effects: skin reactions, otitis media, mild headache, nausea, and vomiting. People with LGG who underwent early radiotherapy showed an increase in time to progression compared with people who were observed and had radiotherapy at the time of progression. There was no significant difference in overall survival between people who had early versus delayed radiotherapy; however, this finding may be due to the effectiveness of rescue therapy with radiation in the control arm. People who underwent early radiation had better seizure control at one year than people who underwent delayed radiation. There were no cases of radiation-induced malignant transformation of LGG. However, it remained unclear whether there were differences in memory, executive function, cognitive function, or quality of life between the two groups since these measures were not evaluated.

Radiation and chemotherapy for high-risk lower grade gliomas: Choosing between temozolomide and PCV

Purpose

The majority of patients with high‐risk lower grade gliomas (LGG) are treated with single‐agent temozolomide (TMZ) and radiotherapy despite three randomized trials showing a striking overall survival benefit with adjuvant procarbazine, lomustine, and vincristine (PCV) chemotherapy and radiotherapy. This article aims to evaluate the evidence and rationale for the widespread use of TMZ instead of PCV for high‐risk LGG.

Methods and Materials

We conducted a literature search utilizing PubMed for articles investigating the combination of radiotherapy and chemotherapy for high‐risk LGG and analyzed the results of these studies.

Results

For patients with IDH mutant 1p/19q codeleted LGG tumors, there is limited evidence to support the use of TMZ. In medically fit patients with codeleted disease, existing data demonstrate a large survival benefit for PCV as compared to adjuvant radiation therapy alone. For patients with non‐1p/19q codeleted LGG, early data from the CATNON study supports inclusion of adjuvant TMZ for 12 months. Subset analyses of the RTOG 9402 and EORTC 26951 do not demonstrate a survival benefit for adjuvant PCV for non‐1p/19q codeleted gliomas, however secondary analyses of RTOG 9802 and RTOG 9402 demonstrated survival benefit in any IDH mutant lower grade gliomas, regardless of 1p/19q codeletion status.

Conclusions

At present, we conclude that current evidence does not support the widespread use of TMZ over PCV for all patients with high‐risk LGG, and we instead recommend tailoring chemotherapy recommendation based on IDH status, favoring adjuvant PCV for patients with any IDH mutant tumors, both those that harbor 1p/19q codeletion and those non‐1p/19q codeleted. Given the critical role radiation plays in the treatment of LGG, radiation oncologists should be actively involved in discussions regarding chemotherapy choice in order to optimize treatment for their patients.

Integrated systems-genetic analyses reveal a network target for delaying glioma progression

Objective

To identify a convergent, multitarget proliferation characteristic for astrocytoma transformation that could be targeted for therapy discovery.

Methods

Using an integrated functional genomics approach, we prioritized networks associated with astrocytoma progression using the following criteria: differential co‐expression between grade II and grade III IDH1‐mutated and 1p/19q euploid astrocytomas, preferential enrichment for genetic risk to cancer, association with patient survival and sample‐level genomic features. Drugs targeting the identified multitarget network characteristic for astrocytoma transformation were computationally predicted using drug transcriptional perturbation data and validated using primary human astrocytoma cells.

Results

A single network, M2, consisting of 177 genes, was associated with glioma progression on the basis of the above criteria. Functionally, M2 encoded physically interacting proteins regulating cell cycle processes and analysis of genome‐wide gene‐regulatory interactions using mutual information and DNA–protein interactions revealed the known regulators of cell cycle processes FoxM1, B‐Myb, and E2F2 as key regulators of M2. These results suggest functional disruption of M2 via gene mutation or altered expression as a convergent pathway regulating astrocytoma transformation. By considering M2 as a multitarget drug target regulating astrocytoma transformation, we identified several drugs that are predicted to restore M2 expression in anaplastic astrocytoma toward its low‐grade profile and of these, we validated the known antiproliferative drug resveratrol as down‐regulating multiple nodes of M2 including at nanomolar concentrations achievable in human cerebrospinal fluid by oral dosing.

Interpretation

Our results identify M2 as a multitarget network characteristic for astrocytoma progression and encourage M2‐based drug screening to identify new compounds for preventing glioma transformation.

Diagnosing growth in low-grade gliomas with and without longitudinal volume measurements: A retrospective observational study

BACKGROUND

Low-grade gliomas cause significant neurological morbidity by brain invasion. There is no universally accepted objective technique available for detection of enlargement of low-grade gliomas in the clinical setting; subjective evaluation by clinicians using visual comparison of longitudinal radiological studies is the gold standard. The aim of this study is to determine whether a computer-assisted diagnosis (CAD) method helps physicians detect earlier growth of low-grade gliomas.

METHODS AND FINDINGS

We reviewed 165 patients diagnosed with grade 2 gliomas, seen at the University of Alabama at Birmingham clinics from 1 July 2017 to 14 May 2018. MRI scans were collected during the spring and summer of 2018. Fifty-six gliomas met the inclusion criteria, including 19 oligodendrogliomas, 26 astrocytomas, and 11 mixed gliomas in 30 males and 26 females with a mean age of 48 years and a range of follow-up of 150.2 months (difference between highest and lowest values). None received radiation therapy. We also studied 7 patients with an imaging abnormality without pathological diagnosis, who were clinically stable at the time of retrospective review (14 May 2018). This study compared growth detection by 7 physicians aided by the CAD method with retrospective clinical reports. The tumors of 63 patients (56 + 7) in 627 MRI scans were digitized, including 34 grade 2 gliomas with radiological progression and 22 radiologically stable grade 2 gliomas. The CAD method consisted of tumor segmentation, computing volumes, and pointing to growth by the online abrupt change-of-point method, which considers only past measurements. Independent scientists have evaluated the segmentation method. In 29 of the 34 patients with progression, the median time to growth detection was only 14 months for CAD compared to 44 months for current standard of care radiological evaluation (p < 0.001). Using CAD, accurate detection of tumor enlargement was possible with a median of only 57% change in the tumor volume as compared to a median of 174% change of volume necessary to diagnose tumor growth using standard of care clinical methods (p < 0.001). In the radiologically stable group, CAD facilitated growth detection in 13 out of 22 patients. CAD did not detect growth in the imaging abnormality group. The main limitation of this study was its retrospective design; nevertheless, the results depict the current state of a gold standard in clinical practice that allowed a significant increase in tumor volumes from baseline before detection. Such large increases in tumor volume would not be permitted in a prospective design. The number of glioma patients (n = 56) is a limitation; however, it is equivalent to the number of patients in phase II clinical trials.

CONCLUSIONS

The current practice of visual comparison of longitudinal MRI scans is associated with significant delays in detecting growth of low-grade gliomas. Our findings support the idea that physicians aided by CAD detect growth at significantly smaller volumes than physicians using visual comparison alone. This study does not answer the questions whether to treat or not and which treatment modality is optimal. Nonetheless, early growth detection sets the stage for future clinical studies that address these questions and whether early therapeutic interventions prolong survival and improve quality of life.

Relationship of In Vivo MR Parameters to Histopathological and Molecular Characteristics of Newly Diagnosed, Nonenhancing Lower-Grade Gliomas

The goal of this research was to elucidate the relationship between WHO 2016 molecular classifications of newly diagnosed, nonenhancing lower grade gliomas (LrGG), tissue sample histopathology, and magnetic resonance (MR) parameters derived from diffusion, perfusion, and ¹H spectroscopic imaging from the tissue sample locations and the entire tumor. A total of 135 patients were scanned prior to initial surgery, with tumor cellularity scores obtained from 88 image-guided tissue samples. MR parameters were obtained from corresponding sample locations, and histograms of normalized MR parameters within the T2 fluid-attenuated inversion recovery lesion were analyzed in order to evaluate differences between subgroups. For tissue samples, higher tumor scores were related to increased normalized apparent diffusion coefficient (nADC), lower fractional anisotropy (nFA), lower cerebral blood volume (nCBV), higher choline (nCho), and lower N-acetylaspartate (nNAA). Within the T2 lesion, higher tumor grade was associated with higher nADC, lower nFA, and higher Cho to NAA index. Pathological analysis confirmed that diffusion and metabolic parameters increased and perfusion decreased with tumor cellularity. This information can be used to select targets for tissue sampling and to aid in making decisions about treating residual disease.

MRI Features and IDH Mutational Status of Grade II Diffuse Gliomas: Impact on Diagnosis and Prognosis

OBJECTIVE

Grade II diffuse gliomas (DGs) with isocitrate dehydrogenase (IDH) mutations are associated with better prognosis than their IDH wild-type counterparts. We sought to determine the MRI characteristics associated with IDH mutational status and ascertain whether MRI considered in combination with IDH mutational status can better predict the clinical outcomes of grade II DGs.

MATERIALS AND METHODS

Preoperative MRI examinations were retrospectively studied for qualitative tumor characteristics, including location, extent, cortical involvement, margin sharpness, cystic component, mineralization or hemorrhage, and contrast enhancement. Quantitative diffusion and perfusion metrics were also assessed. Logistic regression and ROC analyses were used to evaluate the relationship between MRI features and IDH mutational status. The association between IDH mutational status, 1p19q codeletion, MRI features, extent of resection, and clinical outcomes was assessed by Kaplan-Meier and Cox proportional hazards models.

RESULTS

Of 100 grade II DGs, 78 were IDH mutant and 22 were IDH wild type. IDH wild-type tumors were associated with older age, multifocality, brainstem involvement, lack of cystic change, and a lower apparent diffusion coefficient (ADC). Multivariable regression showed that age older than 45 years as well as low minimum ADC (ADC_min), mean ADC, and maximum ADC values were independently associated with IDH mutational status. Of these, an ADC_min threshold of 0.9 × 10^-3 mm²/s or less provided the greatest sensitivity and specificity (91% and 76%, respectively) in defining IDH wild-type grade II DGs. Combining low ADC_min with IDH wild-type status conferred worse outcomes than did IDH wild-type status alone.

CONCLUSION

IDH wild-type grade II DGs are associated with a lower ADC and poor clinical outcomes. Combining IDH mutational status and ADC may allow more accurate prediction of clinical outcomes for patients with grade II DGs.

Differentiation of grade II/III and grade IV glioma by combining "T1 contrast-enhanced brain perfusion imaging" and susceptibility-weighted quantitative imaging

PURPOSE

MRI is a useful method for discriminating low- and high-grade glioma using perfusion MRI and susceptibility-weighted imaging (SWI). The purpose of this study is to evaluate the usefulness of T1-perfusion MRI and SWI in discriminating among grade II, III, and IV gliomas.

METHODS

T1-perfusion MRI was used to measure relative cerebral blood volume (rCBV) in 129 patients with glioma (70 grade IV, 33 grade III, and 26 grade II tumors). SWI was also used to measure the intratumoral susceptibility signal intensity (ITSS) scores for each tumor in these patients. rCBV and ITSS values were compared to seek differences between grade II vs. grade III, grade III vs. grade IV, and grade III+II vs. grade IV tumors.

RESULTS

Significant differences in rCBV values of the three grades of the tumors were noted and pairwise comparisons showed significantly higher rCBV values in grade IV tumors as compared to grade III tumors, and similarly increased rCBV was seen in the grade III tumors as compared to grade II tumors (p < 0.001). Grade IV gliomas showed significantly higher ITSS scores on SWI as compared to grade III tumors (p < 0.001) whereas insignificant difference was seen on comparing ITSS scores of grade III with grade II tumors. Combining the rCBV and ITSS resulted in significant improvement in the discrimination of grade III from grade IV tumors.

CONCLUSION

The combination of rCBV values derived from T1-perfusion MRI and SWI derived ITSS scores improves the diagnostic accuracy for discrimination of grade III from grade IV gliomas.

Current Clinical Brain Tumor Imaging

Neuroimaging plays an ever evolving role in the diagnosis, treatment planning, and post-therapy assessment of brain tumors. This review provides an overview of current magnetic resonance imaging (MRI) methods routinely employed in the care of the brain tumor patient. Specifically, we focus on advanced techniques including diffusion, perfusion, spectroscopy, tractography, and functional MRI as they pertain to noninvasive characterization of brain tumors and pretreatment evaluation. The utility of both structural and physiological MRI in the post-therapeutic brain evaluation is also reviewed with special attention to the challenges presented by pseudoprogression and pseudoresponse.

Multiple-response regression analysis links magnetic resonance imaging features to de-regulated protein expression and pathway activity in lower grade glioma

BACKGROUND AND PURPOSE

Lower grade gliomas (LGGs), lesions of WHO grades II and III, comprise 10-15% of primary brain tumors. In this first-of-a-kind study, we aim to carry out a radioproteomic characterization of LGGs using proteomics data from the TCGA and imaging data from the TCIA cohorts, to obtain an association between tumor MRI characteristics and protein measurements. The availability of linked imaging and molecular data permits the assessment of relationships between tumor genomic/proteomic measurements with phenotypic features.

MATERIALS AND METHODS

Multiple-response regression of the image-derived, radiologist scored features with reverse-phase protein array (RPPA) expression levels generated correlation coefficients for each combination of image-feature and protein or phospho-protein in the RPPA dataset. Significantly-associated proteins for VASARI features were analyzed with Ingenuity Pathway Analysis software. Hierarchical clustering of the results of the pathway analysis was used to determine which feature groups were most strongly correlated with pathway activity and cellular functions.

RESULTS

The multiple-response regression approach identified multiple proteins associated with each VASARI imaging feature. VASARI features were found to be correlated with expression of IL8, PTEN, PI3K/Akt, Neuregulin, ERK/MAPK, p70S6K and EGF signaling pathways.

CONCLUSION

Radioproteomics analysis might enable an insight into the phenotypic consequences of molecular aberrations in LGGs.

Diffuse low-grade glioma: a review on the new molecular classification, natural history and current management strategies

The management of diffuse supratentorial WHO grade II glioma remains a challenge because of the infiltrative nature of the tumor, which precludes curative therapy after total or even supratotal resection. When possible, functional-guided resection is the preferred initial treatment. Total and subtotal resections correlate with increased overall survival. High-risk patients (age >40, partial resection), especially IDH-mutated and 1p19q-codeleted oligodendroglial lesions, benefit from surgery plus adjuvant chemoradiation. Under the new 2016 WHO brain tumor classification, which now incorporates molecular parameters, all diffusely infiltrating gliomas are grouped together since they share specific genetic mutations and prognostic factors. Although low-grade gliomas cannot be regarded as benign tumors, large observational studies have shown that median survival can actually be doubled if an early, aggressive, multi-stage and personalized therapy is applied, as compared to prior wait-and-see policy series. Patients need an honest long-term therapeutic strategy that should ideally anticipate neurological, cognitive and histopathologic worsening.