Imaging Genomics in Glioblastoma Multiforme

Radiogenomic biomarkers for immunotherapy in glioblastoma: A systematic review of magnetic resonance imaging studies

Background

Immunotherapy is an effective "precision medicine" treatment for several cancers. Imaging signatures of the underlying genome (radiogenomics) in glioblastoma patients may serve as preoperative biomarkers of the tumor-host immune apparatus. Validated biomarkers would have the potential to stratify patients during immunotherapy clinical trials, and if trials are beneficial, facilitate personalized neo-adjuvant treatment. The increased use of whole genome sequencing data, and the advances in bioinformatics and machine learning make such developments plausible. We performed a systematic review to determine the extent of development and validation of immune-related radiogenomic biomarkers for glioblastoma.

Methods

A systematic review was performed following PRISMA guidelines using the PubMed, Medline, and Embase databases. Qualitative analysis was performed by incorporating the QUADAS 2 tool and CLAIM checklist. PROSPERO registered: CRD42022340968. Extracted data were insufficiently homogenous to perform a meta-analysis.

Results

Nine studies, all retrospective, were included. Biomarkers extracted from magnetic resonance imaging volumes of interest included apparent diffusion coefficient values, relative cerebral blood volume values, and image-derived features. These biomarkers correlated with genomic markers from tumor cells or immune cells or with patient survival. The majority of studies had a high risk of bias and applicability concerns regarding the index test performed.

Conclusions

Radiogenomic immune biomarkers have the potential to provide early treatment options to patients with glioblastoma. Targeted immunotherapy, stratified by these biomarkers, has the potential to allow individualized neo-adjuvant precision treatment options in clinical trials. However, there are no prospective studies validating these biomarkers, and interpretation is limited due to study bias with little evidence of generalizability.

EGFRvIII peptide nanocapsules and bevacizumab nanocapsules: a nose-to-brain multitarget approach against glioblastoma

Aim: To evaluate the antitumor efficacy of bevacizumab-functionalized nanocapsules in a rat glioblastoma model after the pretreatment with nanocapsules functionalized with a peptide-specific to the epidermal growth factor receptor variant III. Materials & methods: Nanocapsules were prepared, physicochemical characterized and intranasally administered to rats. Parameters such as tumor size, histopathological characteristics and infiltration of CD8⁺ T lymphocytes were evaluated. Results: The strategy of treatment resulted in a reduction of 87% in the tumor size compared with the control group and a higher infiltration of CD8⁺ T lymphocytes in tumoral tissue. Conclusion: The block of two different molecular targets using nose-to-brain delivery represents a new and promising approach against glioblastoma.

Apoptosis related microRNAs and MGMT in glioblastoma cell lines submitted to treatments with ionizing radiation and temozolomide

Aim

To evaluate the effect of radiotherapy and temozolomide on the expression of miRNAs apoptotic (miRNAs-21, -221, -222 (anti-apoptotic) and miRNAs-15a, -16 (pro-apoptotic)) and the gene MGMT in glioblastoma cell lines.

Background

The limited knowledge of the molecular biology of malignant gliomas may hinder the development of therapeutic modalities. In this scenario, one of the greatest advances of recent years was the identification of microRNAs. These molecules have an important role in biological processes involving cancer, including glioblastoma.

Materials and methods

Trypan blue was used to verify the cell viability, and real time PCR to quantify the expression of microRNAs and gene 24, 48 and 120 h after exposure to treatments.

Results

There was a statistically significant decrease of expression of miR-15a between 48 and 120 h in line T98 G treated with radiation, increased expression of miR-15a between 24 and 120 h in line U251 treated with radiation and temozolomide, and increased expression of miR-16 between 24 and 120 h in line U251 treated with radiation alone and when combined with temozolomide. There was a decrease in MGMT gene expression, between 24 and 48 h in U343 cells treated with temozolomide.

Conclusions

Ionizing radiation and temozolomide modified the expression of miRNAs studied and MGMT.

Pre-operative Overall Survival Time Prediction for Glioblastoma Patients Using Deep Learning on Both Imaging Phenotype and Genotype

Glioblastoma (GBM) is the most common and deadly malignant brain tumor with short yet varied overall survival (OS) time. Per request of personalized treatment, accurate pre-operative prognosis for GBM patients is highly desired. Currently, many machine learning-based studies have been conducted to predict OS time based on pre-operative multimodal MR images of brain tumor patients. However, tumor genotype, such as MGMT and IDH, which has been proven to have strong relationship with OS, is completely not considered in pre-operative prognosis as the genotype information is unavailable until craniotomy. In this paper, we propose a new deep learning based method for OS time prediction. It can derive genotype related features from pre-operative multimodal MR images of brain tumor patients to guide OS time prediction. Particularly, we propose a multi-task convolutional neural network (CNN) to accomplish tumor genotype and OS time prediction tasks. As the network can benefit from learning genotype related features toward genotype prediction, we verify upon a dataset of 120 GBM patients and conclude that the multi-task learning can effectively improve the accuracy of predicting OS time in personalized prognosis.

Prognostic significance of epidermal growth factor receptor expression in glioma patients

Purpose

There is a great controversy regarding the prognostic significance of epidermal growth factor receptor (EGFR) in glioma patients. The current meta-analysis was conducted to evaluate the effect of abnormal EGFR expression on overall survival in glioma patients.

Materials and methods

A comprehensive literature search of PubMed, EMBASE, Google Scholar, Web of Science, and Cochrane Library was conducted. The combined hazard ratio (HR) and its 95% confidence intervals (CIs) were used to evaluate the association between EGFR expression and survival in glioma.

Results

A total of 476 articles were screened, and 17 articles containing 1,458 patients were selected. The quality assessment of the included studies was performed by the Newcastle-Ottawa Scale. Overexpression of EGFR was found to be an indicator of poor prognosis in overall survival in glioma patients (HR =1.72, 95% CI 1.32-2.25, P=0.000, random effect) and glioblastoma multiforme patients (HR =1.57, 95% CI 1.15-2.14, P=0.004, random effect). Subgroup analysis was conducted to explore the source of high heterogeneity.

Conclusion

This meta-analysis indicated that high expression of EGFR may serve as a biomarker for poor prognosis in glioma patients.

From imaging to biology of glioblastoma: new clinical oncology perspectives to the problem of local recurrence

GBM is one of the most common and aggressive brain tumors. Surgery and adjuvant chemoradiation have succeeded in providing a survival benefit. Although most patients will eventually experience local recurrence, the means to fight recurrence are limited and prognosis remains poor. In a disease where local control remains the major challenge, few trials have addressed the efficacy of local treatments, either surgery or radiation therapy. The present article reviews recent advances in the biology, imaging and biomarker science of GBM as well as the current treatment status of GBM, providing new perspectives to the problem of local recurrence.