Incorporation of biomarker assessment in novel clinical trial designs: personalizing brain tumor treatments

BICD Cargo Adaptor 1 (BICD1) Downregulation Correlates with a Decreased Level of PD-L1 and Predicts a Favorable Prognosis in Patients with IDH1-Mutant Lower-Grade Gliomas

Simple Summary

The hypoxic inducible factor 1A (HIF1A) pathway has been known to play an important role in tumor progression in various cancers, including lower-grade (Grade II/III) gliomas (LGGs). An in silico analysis using 34 genes associated with the activity of the HIF1A pathway demonstrated that the BICD cargo adaptor 1 (BICD1) gene is a potential prognostic marker in LGGs. Moreover, BICD1 gene (BICD1) expression was positively correlated with CD274, GSK3B, HGF, and STAT3 expression in LGGs. Importantly, BICD1 downregulation was significantly associated with well-known favorable prognostic markers, such as a higher Karnofsky performance score (KPS), IDH1/TP53/ATRX mutations, wild-type EGFR and younger patient age, in LGGs. Therefore, our findings present BICD1 as a new prognostic biomarker to more precisely predict the clinical outcomes of LGG patients in coordination with those well-known biomarkers.

Abstract

Although several biomarkers have been identified to predict the prognosis of lower-grade (Grade II/III) gliomas (LGGs), we still need to identify new markers to facilitate those well-known markers to obtain more accurate prognosis prediction in LGGs. Bioinformatics data from The Cancer Genome Atlas (TCGA), the Chinese Glioma Genome Atlas (CGGA), and the Cancer Cell Line Encyclopedia (CCLE) datasets were used as the research materials. In total, 34 genes associated with the HIF1A pathway were analyzed using the hierarchical method to search for the most compatible gene. The BICD cargo adaptor 1 (BICD1) gene (BICD1) was shown to be significantly correlated with The hypoxic inducible factor 1A (HIF1A) expression, the World Health Organization (WHO) grade, and IDH1 mutation status. In addition, BICD1 downregulation was significantly correlated with a higher Karnofsky performance score (KPS), IDH1/TP53/ATRX mutations, wild-type EGFR, and younger patient age in the enrolled LGG cohort. Moreover, BICD1 expression was significantly upregulated in wild-type IDH1 LGGs with EGFR mutations. Kaplan–Meier survival analysis revealed that BICD1 downregulation predicts a favorable overall survival (OS) in LGG patients, especially in those with IDH1 mutations. Intriguingly, we found a significant correlation between BICD1 downregulation and a decreased level of CD274, GSK3B, HGF, or STAT3 in LGGs. Our findings suggest that BICD1 downregulation could be a potential biomarker for a favorable prognosis of LGGs.

Integrating Genomics Into Neuro-Oncology Clinical Trials and Practice

Important advances in our understanding of the molecular biology of brain tumors have resulted in a rapid evolution in the taxonomy of central nervous system (CNS) tumors, which culminated in the revised 2016 World Health Organization classification of CNS tumors that incorporates an integrated molecular/histologic diagnostic approach. Our expanding understanding of brain tumor genomics and molecular evolution during the disease course has started to impact clinical management. Furthermore, incorporation of genomic information in ongoing and planned neuro-oncology clinical trials is expected to lead to improved outcomes and result in personalized treatment options for patients with CNS malignancies.

BICD1 expression, as a potential biomarker for prognosis and predicting response to therapy in patients with glioblastomas

There is variation in the survival and therapeutic outcome of patients with glioblastomas (GBMs). Therapy resistance is an important challenge in the treatment of GBM patients. The aim of this study was to identify Temozolomide (TMZ) related genes and confirm their clinical relevance. The TMZ-related genes were discovered by analysis of the gene-expression profiling in our cell-based microarray. Their clinical relevance was verified by in silico meta-analysis of the Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) datasets. Our results demonstrated that BICD1 expression could predict both prognosis and response to therapy in GBM patients. First, high BICD1 expression was correlated with poor prognosis in the TCGA GBM cohort (n=523) and in the CGGA glioma cohort (n=220). Second, high BICD1 expression predicted poor outcome in patients with TMZ treatment (n=301) and radiation therapy (n=405). Third, multivariable Cox regression analysis confirmed BICD1 expression as an independent factor affecting the prognosis and therapeutic response of TMZ and radiation in GBM patients. Additionally, age, MGMT and BICD1 expression were combinedly utilized to stratify GBM patients into more distinct risk groups, which may provide better outcome assessment. Finally, we observed a strong correlation between BICD1 expression and epithelial-mesenchymal transition (EMT) in GBMs, and proposed a possible mechanism of BICD1-associated survival or therapeutic resistance in GBMs accordingly. In conclusion, our study suggests that high BICD1 expression may result in worse prognosis and could be a predictor of poor response to TMZ and radiation therapies in GBM patients.

Biomarker-Guided Non-Adaptive Trial Designs in Phase II and Phase III: A Methodological Review

Biomarker-guided treatment is a rapidly developing area of medicine, where treatment choice is personalised according to one or more of an individual’s biomarker measurements. A number of biomarker-guided trial designs have been proposed in the past decade, including both adaptive and non-adaptive trial designs which test the effectiveness of a biomarker-guided approach to treatment with the aim of improving patient health. A better understanding of them is needed as challenges occur both in terms of trial design and analysis. We have undertaken a comprehensive literature review based on an in-depth search strategy with a view to providing the research community with clarity in definition, methodology and terminology of the various biomarker-guided trial designs (both adaptive and non-adaptive designs) from a total of 211 included papers. In the present paper, we focus on non-adaptive biomarker-guided trial designs for which we have identified five distinct main types mentioned in 100 papers. We have graphically displayed each non-adaptive trial design and provided an in-depth overview of their key characteristics. Substantial variability has been observed in terms of how trial designs are described and particularly in the terminology used by different authors. Our comprehensive review provides guidance for those designing biomarker-guided trials.

IQGAP1 in Podosomes/Invadosomes Is Involved in the Progression of Glioblastoma Multiforme Depending on the Tumor Status

Glioblastoma multiforme (GBM) is the most frequent and aggressive primary brain tumor. GBM is formed by a very heterogeneous astrocyte population, neurons, neovascularization and infiltrating myeloid cells (microglia and monocyte derived macrophages). The IQGAP1 scaffold protein interacts with components of the cytoskeleton, cell adhesion molecules, and several signaling molecules to regulate cell morphology and motility, cell cycle and other cellular functions. IQGAP1 overexpression and delocalization has been observed in several tumors, suggesting a role for this protein in cell proliferation, transformation and invasion. IQGAP1 has been identified as a marker of amplifying cancer cells in GBMs. To determine the involvement of IQGAP1 in the onco-biology of GBM, we performed immunohistochemical confocal microscopic analysis of the IQGAP1 protein in human GBM tissue samples using cell type-specific markers. IQGAP1 immunostaining and subcellular localization was heterogeneous; the protein was located in the plasma membrane and, at variable levels, in nucleus and/or cytosol. Moreover, IQGAP1 positive staining was found in podosome/invadopodia-like structures. IQGAP1⁺ staining was observed in neurons (Map2⁺ cells), in cancer stem cells (CSC; nestin⁺) and in several macrophages (CD31⁺ or Iba1⁺). Our results indicate that the IQGAP1 protein is involved in normal cell physiology as well as oncologic processes.

Biomarker-Guided Adaptive Trial Designs in Phase II and Phase III: A Methodological Review

BACKGROUND

Personalized medicine is a growing area of research which aims to tailor the treatment given to a patient according to one or more personal characteristics. These characteristics can be demographic such as age or gender, or biological such as a genetic or other biomarker. Prior to utilizing a patient's biomarker information in clinical practice, robust testing in terms of analytical validity, clinical validity and clinical utility is necessary. A number of clinical trial designs have been proposed for testing a biomarker's clinical utility, including Phase II and Phase III clinical trials which aim to test the effectiveness of a biomarker-guided approach to treatment; these designs can be broadly classified into adaptive and non-adaptive. While adaptive designs allow planned modifications based on accumulating information during a trial, non-adaptive designs are typically simpler but less flexible.

METHODS AND FINDINGS

We have undertaken a comprehensive review of biomarker-guided adaptive trial designs proposed in the past decade. We have identified eight distinct biomarker-guided adaptive designs and nine variations from 107 studies. Substantial variability has been observed in terms of how trial designs are described and particularly in the terminology used by different authors. We have graphically displayed the current biomarker-guided adaptive trial designs and summarised the characteristics of each design.

CONCLUSIONS

Our in-depth overview provides future researchers with clarity in definition, methodology and terminology for biomarker-guided adaptive trial designs.

Rhamnose-coated superparamagnetic iron-oxide nanoparticles: an evaluation of their in vitro cytotoxicity, genotoxicity and carcinogenicity

Tumor recurrence after the incomplete removal of a tumor mass inside brain tissue is the main reason that scientists are working to identify new strategies in brain oncologic therapy. In particular, in the treatment of the most malignant astrocytic tumor glioblastoma, the use of magnetic nanoparticles seems to be one of the most promising keys in overcoming this problem, namely by means of magnetic fluid hyperthermia (MFH) treatment. However, the major unknown issue related to the use of nanoparticles is their toxicological behavior when they are in contact with biological tissues. In the present study, we investigated the interaction of glioblastoma and other tumor cell lines with superparamagnetic iron-oxide nanoparticles covalently coated with a rhamnose derivative, using proper cytotoxic assays. In the present study, we focused our attention on different strategies of toxicity evaluation comparing different cytotoxicological approaches in order to identify the biological damages induced by the nanoparticles. The data show an intensive internalization process of rhamnose-coated iron oxide nanoparticles by the cells, suggesting that rhamnose moiety is a promising biocompatible coating in favoring cells' uptake. With regards to cytotoxicity, a 35% cell death at a maximum concentration, mainly as a result of mitochondrial damages, was found. This cytotoxic behavior, along with the high uptake ability, could facilitate the use of these rhamnose-coated iron-oxide nanoparticles for future MFH therapeutic treatments.

Current Challenges in Glioblastoma: Intratumour Heterogeneity, Residual Disease, and Models to Predict Disease Recurrence

Glioblastoma (GB) is the most common primary malignant brain tumor, and despite the availability of chemotherapy and radiotherapy to combat the disease, overall survival remains low with a high incidence of tumor recurrence. Technological advances are continually improving our understanding of the disease, and in particular, our knowledge of clonal evolution, intratumor heterogeneity, and possible reservoirs of residual disease. These may inform how we approach clinical treatment and recurrence in GB. Mathematical modeling (including neural networks) and strategies such as multiple sampling during tumor resection and genetic analysis of circulating cancer cells, may be of great future benefit to help predict the nature of residual disease and resistance to standard and molecular therapies in GB.

Clinical Neuropathology practice guide 5-2015: MGMT methylation pyrosequencing in glioblastoma: unresolved issues and open questions

O6-methylguanine-methyltransferase (MGMT) promoter methylation status has prognostic and, in the subpopulation of elderly patients, predictive value in newly diagnosed glioblastoma. Therefore, knowledge of the MGMT promoter methylation status is important for clinical decision-making. So far, MGMT testing has been limited by the lack of a robust test with sufficiently high analytical performance. Recently, one of several available pyrosequencing protocols has been shown to be an accurate and robust method for MGMT testing in an intra- and interlaboratory ring trial. However, some uncertainties remain with regard to methodological issues, cut-off definitions, and optimal use in the clinical setting. In this article, we highlight and discuss several of these open questions. The main unresolved issues are the definition of the most relevant CpG sites to analyze for clinical purposes and the determination of a cut-off value for dichotomization of quantitative MGMT pyrosequencing results into "MGMT methylated" and "MGMT unmethylated" patient subgroups as a basis for further treatment decisions.

Prognostic and predictive biomarkers in adult and pediatric gliomas: toward personalized treatment

It is increasingly clear that both adult and pediatric glial tumor entities represent collections of neoplastic lesions, each with individual pathological molecular events and treatment responses. In this review, we discuss the current prognostic biomarkers validated for clinical use or with future clinical validity for gliomas. Accurate prognostication is crucial for managing patients as treatments may be associated with high morbidity and the benefits of high risk interventions must be judged by the treating clinicians. We also review biomarkers with predictive validity, which may become clinically relevant with the development of targeted therapies for adult and pediatric gliomas.

Biomarker-based adaptive trials for patients with glioblastoma--lessons from I-SPY 2

The traditional clinical trials infrastructure may not be ideally suited to evaluate the numerous therapeutic hypotheses that result from the increasing number of available targeted agents combined with the various methodologies to molecularly subclassify patients with glioblastoma. Additionally, results from smaller screening studies are rarely translated to successful larger confirmatory studies, potentially related to a lack of efficient control arms or the use of unvalidated surrogate endpoints. Streamlining clinical trials and providing a flexible infrastructure for biomarker development is clearly needed for patients with glioblastoma. The experience developing and implementing the I-SPY studies in breast cancer may serve as a guide to developing such trials in neuro-oncology.

The future of glioma treatment: stem cells, nanotechnology and personalized medicine

The development of novel therapies, imaging techniques and insights into the processes that drive growth of CNS tumors have allowed growing enthusiasm for the treatment of CNS malignancies. Despite this energized effort to investigate and treat brain cancer, clinical outcomes for most patients continue to be dismal. Recognition of diverse tumor subtypes, behaviors and outcomes has led to an interest in personalized medicine for the treatment of brain tumors. This new paradigm requires evaluation of the tumor phenotype at the time of diagnosis so that therapy can be specifically tailored to each individual patient. Investigating novel therapies involving stem cells, nanotechnology and molecular medicine will allow diversity of therapeutic options for patients with brain cancer. These exciting new therapeutic strategies for brain tumors are reviewed in this article.

Phase 2 trial design in neuro-oncology revisited: a report from the RANO group

Advances in the management of gliomas, including the approval of agents such as temozolomide and bevacizumab, have created an evolving therapeutic landscape in glioma treatment, thus affecting our ability to reliably use historical controls to comparatively assess the activity of new therapies. Furthermore, the increasing availability of novel, targeted agents--which are competing for a small patient population, in view of the low incidence of primary brain tumours--draws attention to the need to improve the efficiency of phase 2 clinical testing in neuro-oncology to expeditiously transition the most promising of these drugs or combinations to potentially practice-changing phase 3 trials. In this report from the Response Assessment in Neurooncology (RANO) group, we review phase 2 trial designs that can address these challenges and capitalise on scientific and clinical advances in brain tumour treatment in neuro-oncology to accelerate and optimise the selection of drugs deserving further testing in phase 3 trials. Although there is still a small role for single-arm and non-comparative phase 2 designs, emphasis is placed on the potential role that comparative randomised phase 2 designs--such as screening designs, selection designs, discontinuation designs, and adaptive designs, including seamless phase 2/3 designs--can have. The rational incorporation of these designs, as determined by the specific clinical setting and the trial's endpoints or goals, has the potential to substantially advance new drug development in neuro-oncology.