Predictive markers of immune response in glioblastoma: hopes and facts

Advanced immunotherapies for glioblastoma: tumor neoantigen vaccines in combination with immunomodulators

Glial-origin brain tumors, including glioblastomas (GBM), have one of the worst prognoses due to their rapid and fatal progression. From an oncological point of view, advances in complete surgical resection fail to eliminate the entire tumor and the remaining cells allow a rapid recurrence, which does not respond to traditional therapeutic treatments. Here, we have reviewed new immunotherapy strategies in association with the knowledge of the immune micro-environment. To understand the best lines for the future, we address the advances in the design of neoantigen vaccines and possible new immune modulators. Recently, the efficacy and availability of vaccine development with different formulations, especially liposome plus mRNA vaccines, has been observed. We believe that the application of new strategies used with mRNA vaccines in combination with personalized medicine (guided by different omic's strategies) could give good results in glioma therapy. In addition, a large part of the possible advances in new immunotherapy strategies focused on GBM may be key improving current therapies of immune checkpoint inhibitors (ICI), given the fact that this type of tumor has been highly refractory to ICI.

Impact of molecular and clinical variables on survival outcome with immunotherapy for glioblastoma patients: A systematic review and meta-analysis

BACKGROUND

Given that only a subset of patients with glioblastoma multiforme (GBM) responds to immuno-oncology, this study aimed to assess the impact of multiple factors on GBM immunotherapy prognosis and investigate the potential predictors.

METHODS

A quantitative meta-analysis was conducted using the random-effects model. Several potential factors were also reviewed qualitatively.

RESULTS

A total of 39 clinical trials were included after screening 1317 papers. Patients with O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation [hazard ratio (HR) for overall survival (OS) = 2.30, p < 0.0001; HR for progression-free survival (PFS) = 2.10, p < 0.0001], gross total resection (HR for OS = 0.70, p = 0.02; HR for PFS = 0.56, p = 0.004), and no baseline steroid use (HR for OS = 0.52, p = 0.0002; HR for PFS = 0.61, p = 0.02) had a relatively significant favorable OS and PFS following immunotherapy. Patients with a Karnofsky Performance Status score < 80 (HR = 1.73, p = 0.0007) and undergoing two prior relapses (HR = 2.08, p = 0.003) were associated with worse OS. Age, gender, tumor programmed death-ligand 1 expression, and history of chemotherapy were not associated with survival outcomes. Notably, immunotherapy significantly improved the OS among patients undergoing two prior recurrences (HR = 0.40, p = 0.008) but not among patients in any other subgroups, as opposed to non-immunotherapy.

CONCLUSION

Several factors were associated with prognostic outcomes of GBM patients receiving immunotherapy; multiple recurrences might be a candidate predictor. More marker-driven prospective studies are warranted.

Hypermutation as a potential predictive biomarker of immunotherapy efficacy in high-grade gliomas: a broken dream?

A high tumor mutational burden and mismatch repair deficiency are observed in 'hypermutated' high-grade gliomas (HGGs); however, the molecular characterization of this distinct subtype and whether it predicts the response to immune checkpoint inhibitors (ICIs) are largely unknown. Pembrolizumab is a valid therapeutic option for the treatment of hypermutated cancers of diverse origin, but only a few clinical trials have explored the activity of ICIs in hypermutated HGGs. HGGs appear to differ from other cancers, likely due to the prevalence of subclonal versus clonal neoantigens, which are unable to elicit an immune response with ICIs. The main aim of this review is to summarize the current knowledge on hypermutation in HGGs, focusing on the broken promises of tumor mutational burden and mismatch repair deficiency as potential biomarkers of response to ICIs.

Pharmacotherapeutic Treatment of Glioblastoma: Where Are We to Date?

The clinical management of glioblastoma (GBM) is still bereft of treatments able to significantly improve the poor prognosis of the disease. Despite the extreme clinical need for novel therapeutic drugs, only a small percentage of patients with GBM benefit from inclusion in a clinical trial. Moreover, often clinical studies do not lead to final interpretable conclusions. From the mistakes and negative results obtained in the last years, we are now able to plan a novel generation of clinical studies for patients with GBM, allowing the testing of multiple anticancer agents at the same time. This assumes critical importance, considering that, thanks to improved knowledge of altered molecular mechanisms related to the disease, we are now able to propose several potential effective compounds in patients with both newly diagnosed and recurrent GBM. Among the novel compounds assessed, the initially great enthusiasm toward trials employing immune checkpoint inhibitors (ICIs) was disappointing due to the negative results that emerged in three randomized phase III trials. However, novel biological insights into the disease suggest that immunotherapy can be a convincing and effective treatment in GBM even if ICIs failed to prolong the survival of these patients. In this regard, the most promising approach consists of engineered immune cells such as chimeric antigen receptor (CAR) T, CAR M, and CAR NK alone or in combination with other treatments. In this review, we discuss several issues related to systemic treatments in GBM patients. First, we assess critical issues toward the planning of clinical trials and the strategies employed to overcome these obstacles. We then move on to the most relevant interventional studies carried out on patients with previously untreated (newly diagnosed) GBM and those with recurrent and pretreated disease. Finally, we investigate novel immunotherapeutic approaches with special emphasis on preclinical and clinical data related to the administration of engineered immune cells in GBM.

Glioblastoma Microenvironment: From an Inviolable Defense to a Therapeutic Chance

Glioblastoma is an aggressive tumor and is associated with a dismal prognosis. The availability of few active treatments as well as the inexorable recurrence after surgery are important hallmarks of the disease. The biological behavior of glioblastoma tumor cells reveals a very complex pattern of genomic alterations and is partially responsible for the clinical aggressiveness of this tumor. It has been observed that glioblastoma cells can recruit, manipulate and use other cells including neurons, glial cells, immune cells, and endothelial/stromal cells. The final result of this process is a very tangled net of interactions promoting glioblastoma growth and progression. Nonetheless, recent data are suggesting that the microenvironment can also be a niche in which glioblastoma cells can differentiate into glial cells losing their tumoral phenotype. Here we summarize the known interactions between micro-environment and glioblastoma cells highlighting possible therapeutic implications.

Immune-checkpoint inhibitors in pituitary malignancies

To date, there are no standardized systemic treatment options for patients with metastatic pituitary carcinoma progressed to chemo and radiation therapy. Immune-checkpoint inhibitors (ICIs) have been successfully assessed in other solid malignancies and could be a concrete hope for these patients. We performed a critical review of the literature aimed to evaluate studies assessing ICIs in pituitary malignancies. We also conducted research about published translational data assessing immune-contexture in these malignancies. Some preliminary reports reported a successful administration of pembrolizumab or the combination between nivolumab and ipilimumab in patients with metastatic ACTH-secreting pituitary carcinomas. Translational data suggest that adenomas secreting growth hormone and ACTH have a suppressed immune-microenvironment, which could be more likely to benefit from ICIs. Immune-checkpoint inhibitors can be an effective treatment in patients with pituitary carcinoma and maybe also recurrent adenoma. Tumors secreting growth hormone and ACTH are more likely to benefit from ICIs due to a different immune-microenvironment.

Molecular Features of Glioma Determined and Validated Using Combined TCGA and GTEx Data Analyses

Gliomas are among the most common intracranial tumors which originated from neuroepithelial cells. Increasing evidence has revealed that long noncoding RNA (lncRNA)-microRNA (miRNA)-mRNA module regulation and tumor-infiltrating immune cells play important regulatory roles in the occurrence and progression of gliomas. However, the precise underlying molecular mechanisms remain largely unknown. Data on gliomas in The Cancer Genome Atlas lack normal control samples; to overcome this limitation, we combined 665 The Cancer Genome Atlas glioma RNA sequence datasets with 188 Genotype-Tissue Expression normal brain RNA sequences to construct an expression matrix profile after normalization. We systematically analyzed the expression of mRNAs, lncRNAs, and miRNAs between gliomas and normal brain tissues. Kaplan–Meier survival analyses were conducted to screen differentially expressed mRNAs, lncRNAs, and miRNAs. A prognostic miRNA-related competitive endogenous RNA network was constructed, and the core subnetworks were filtered using 6 miRNAs, 3 lncRNAs, and 11 mRNAs. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed to investigate the biological functions of significantly dysregulated mRNAs. Co-expression network analysis was performed to analyze and screen the core genes. Furthermore, single-sample Gene Set Enrichment Analysis and immune checkpoint gene expression analysis were performed, as co-expression analysis indicated immune gene dysregulation in glioma. Finally, the expression of representative dysregulated genes was validated in U87 cells at the transcriptional level, establishing a foundation for further research. We identified 7017 mRNAs, 437 lncRNAs, and 9 miRNAs that were differentially expressed in gliomas. Kaplan–Meier survival analysis revealed 5684 mRNAs, 61 lncRNAs, and 7 miRNAs with potential as prognostic signatures in patients with glioma. The hub subnetwork of the competing endogenous RNA network between PART1-hsa-mir-25-SLC12A5/TACC2/BSN/TLN2/ZDHHC8 was screened out. Gene co-expression network, single-sample Gene Set Enrichment Analysis, and immune checkpoint expression analysis demonstrated that tumor-infiltrating immune cells are closely related to gliomas. We identified novel potential biomarkers to predict survival and therapeutic targets for patients with gliomas based on a large-scale sample. Importantly, we filtered pivotal genes that provide valuable information for further exploration of the molecular mechanisms underlying glioma tumorigenesis and progression.

Radiomics, mirnomics, and radiomirRNomics in glioblastoma: defining tumor biology from shadow to light

INTRODUCTION

Glioblastoma is a highly aggressive brain tumor with an extremely poor prognosis. Genetic characterization of this tumor has identified alterations with prognostic and therapeutic impact, and many efforts are being made to improve molecular knowledge on glioblastoma. Invasive procedures, such as tumor biopsy or radical resection, are needed to characterize the tumor.

AREAS COVERED

The role of microRNA in cancer is an expanding field of research as many microRNAs have been shown to correlate with patient prognosis and treatment response. Novel methodologies like radiomics, radiogenomics, and radiomiRNomics are under evaluation to improve the amount of prognostic and predictive biomarkers available.

EXPERT OPINION

The role of radiomics, radiogenomics, and radiomiRNomic for the characterization of glioblastoma will further improve in the coming years.

Glioblastoma: Emerging Treatments and Novel Trial Designs

Simple Summary

Nowadays, very few systemic agents have shown clinical activity in patients with glioblastoma, making the research of novel therapeutic approaches a critical issue. Fortunately, the availability of novel compounds is increasing thanks to better biological knowledge of the disease. In this review we want to investigate more promising ongoing clinical trials in both primary and recurrent GBM. Furthermore, a great interest of the present work is focused on novel trial design strategies.

Abstract

Management of glioblastoma is a clinical challenge since very few systemic treatments have shown clinical efficacy in recurrent disease. Thanks to an increased knowledge of the biological and molecular mechanisms related to disease progression and growth, promising novel treatment strategies are emerging. The expanding availability of innovative compounds requires the design of a new generation of clinical trials, testing experimental compounds in a short time and tailoring the sample cohort based on molecular and clinical behaviors. In this review, we focused our attention on the assessment of promising novel treatment approaches, discussing novel trial design and possible future fields of development in this setting.

Predicting clinical outcomes using cancer progression associated signatures

Somatic mutation signatures are an informative facet of cancer aetiology, however they are rarely useful for predicting patient outcome. The aim of this study is to evaluate the utility of a panel of 142 mutation-signature–associated metrics (P142) for predicting cancer progression in patients from a ‘TCGA PanCancer Atlas’ cohort. The P142 metrics are comprised of AID/APOBEC and ADAR deaminase associated SNVs analyzed for codon context, strand bias, and transitions/transversions. TCGA tumor-normal mutation data was obtained for 10,437 patients, representing 31 of the most prevalent forms of cancer. Stratified random sampling was used to split patients into training, tuning and validation cohorts for each cancer type. Cancer specific machine learning (XGBoost) models were built using the output from the P142 panel to predict patient Progression Free Survival (PFS) status as either “High PFS” or “Low PFS”. Predictive performance of each model was evaluated using the validation cohort. Models accurately predicted PFS status for several cancer types, including adrenocortical carcinoma, glioma, mesothelioma, and sarcoma. In conclusion, the P142 panel of metrics successfully predicted cancer progression status in patients with some, but not all cancer types analyzed. These results pave the way for future studies on cancer progression associated signatures.

Treatment of recurrent glioblastoma: state-of-the-art and future perspectives

BACKGROUND

Almost all patients affected by glioblastoma experience recurrence of the disease.

AREAS COVERED

Management of recurrent glioblastoma is a clinical challenge, and several elements should be taken into consideration when making treatment choice. Loco-regional treatments may be the best treatment approach in selected cases while systemic therapies or supportive care alone are necessary for other patients. Unfortunately, few drugs have shown clinical in this setting. This lack of effective treatments has made recurrent glioblastoma a disease orphan of an effective approach.

EXPERT OPINION

Results of recent clinical trials offer interesting perspectives and may controvert this axiom.