Should biomarkers be used to design personalized medicine for the treatment of glioblastoma?

Final Results of the Prospective Biomarker Trial PETra: [11C]-MET-Accumulation in Postoperative PET/MRI Predicts Outcome after Radiochemotherapy in Glioblastoma

PURPOSE

This prospective trial investigates the association of time to recurrence (TTR) in glioblastoma with [¹¹C]methionine (MET) tracer uptake before postoperative radiochemotherapy (RCT) aiming to guide radiotherapy boost regions.

EXPERIMENTAL DESIGN

Between 2013 and 2016, 102 patients with glioblastoma were recruited. RCT was performed with concurrent and adjuvant temozolomide to a total dose of 60 Gy. Tumor residues in postresection PET and MRI were together defined as gross tumor volumes for radiotherapy treatment planning. [¹¹C]methionine (MET)-PET/MRI was performed before RCT and at each follow-up.

RESULTS

The primary hypothesis of a longer TTR for patients without increased tracer accumulation in postoperative MET-PET was confirmed in 89 patients. With 18.9 months (95% confidence interval, 9.3-28.5 months), median TTR was significantly (P < 0.001) longer for patients without (n = 29, 32.6%) as compared with 6.3 months (3.6-8.9) for patients with MET accumulation (n = 60, 67.4%) in pre-RCT PET. Although MRI often did not detect all PET-positive regions, an unfavorable impact of residual tumor in postsurgical MRI (n = 38, 42.7%) on TTR was observed [4.6 (4.2-5.1) vs. 15.5 months (6.0-24.9), P < 0.001]. Significant multivariable predictors for TTR were MRI positivity, PET-positive volume, and O⁶-methylguanine DNA methyltransferase (MGMT) hypermethylation.

CONCLUSIONS

Postsurgical amino acid PET has prognostic value for TTR after RCT in glioblastoma. Because of the added value of the metabolic beyond the pure structural information, it should complement MRI in radiotherapy planning if available with reasonable effort, at least in the context of maximal therapy. Furthermore, the spatial correlation of regions of recurrence with PET-positive volumes could provide a bioimaging basis for further trials, for example, testing local radiation dose escalation.

Emergence of exosomal DNA in molecular neuropathology

Background:

Exosomes are small vesicles of sizes between 40 and 100 nm. They are actively segregated by numerous different cell types and they can be found in almost all body fluids. Thus, there is an emerging role of exosomes and exosomal deoxyribonucleic acid (exoDNA) in biomedical research, especially in molecular medicine. Exosomes are assembled and segregated actively and carry distinct surface markers for cellular communication. They are loaded with cargo such as DNA, ribonucleic acid (RNA) and proteins. As there are numerous different exosomal purification methods available, it is of essential need to select an appropriate technique to get reliable results. As neuropathology is faced with the challenge that brain tissue is not accessible in an easy fashion, exosomes represent an ideal tool for molecular neuropathology. Thus, disease-specific molecular alterations will be detectable in a minimally invasive way for early disease diagnosis and surveillance.

Summary:

The analysis of exoDNA as biomarkers in neuropathology will enable early diagnosis, monitoring and relapse detection of brain tumors and neuropsychiatric disorders.

Outlook:

It is assumed that the significance of exosomes will increase in the upcoming years. There are powerful approaches in development using exosomes in molecularly targeted therapy to ultimately cure devastating brain diseases.

Effect of Bevacizumab Plus Temozolomide-Radiotherapy for Newly Diagnosed Glioblastoma with Different MGMT Methylation Status: A Meta-Analysis of Clinical Trials

BACKGROUND MGMT methylation status can influence the therapeutic effect and prognosis of glioblastoma (GBM). There are conflicting results from studies evaluating the efficacy of bevacizumab (BV) when it is combined with temozolomide (TMZ) and radiotherapy (RT) in patients diagnosed with GBM with different MGMT methylation status. MATERIAL AND METHODS Data were extracted from publications in PubMed, Embase, and The Cochrane Library, with the last search performed March 23, 2016. Data on overall survival (OS), progression-free survival (PFS), and MGMT methylation status were obtained. RESULTS Data from 3 clinical trials for a total of 1443 subjects were used for this meta-analysis. MGMT methylated and unmethylated patients showed improved PFS in the BV group (pooled HRs, 0.769, 95% CIs 0.604-0.978, P=0.032; 0.675, 95%CIs 0.466-0.979, P=0.038). For patients with either type of GBM, BV did not improve the OS based on the pooled HRs 1.132 (95% CIs 0.876-1.462; P=0.345) for methylated and 1.018 (95% CIs 0.879-1.179; P=0.345) for unmethylated. CONCLUSIONS Bevacizumab combined with temozolomide-radiotherapy correlated with improved PFS for treatment of patients with different MGMT methylation status of newly diagnosed GBM. There was insufficient evidence to determine the synergistic effects of combining BV with TMZ and RT on improving survival in patients with different MGMT methylation status.

Charlson comorbidity index: an additional prognostic parameter for preoperative glioblastoma patient stratification

PURPOSE

Dismal glioblastoma (GB) patient outcome calls for the elucidation of further reliable predictors of prognosis. Established "biomarkers," age and functional status, employed in today's patient stratification have limits in fingerprinting this heterogeneous tumor entity. We aimed at ascertaining additional prognostic factors that may facilitate patient stratification for surgery.

METHODS

A retrospective review of 233 consecutive adult patients operated on for newly diagnosed GB at a single tertiary institution over a 5-year period (2006-2011) was conducted. Modern defined outcome associating factors recorded included demographics (preoperative age, gender, signs, symptoms, comorbidity status quantified by the Charlson comorbidity index (CCI), functional status computed by the Karnofsky performance scale (KPS)), tumor characteristics (size, location, isocitrate dehydrogenase mutation, and O-6-methylguanine-DNA methyltransferase promoter methylation status), and treatment parameters (volumetrically quantified extent of resection and adjuvant therapy). Survival analysis was performed by the Kaplan-Maier method. Influence of variables was evaluated using log-rank test.

RESULTS

Median neuroradiographic evidence of tumor progression was 6 months after surgery (range 0-72). The median overall survival was 9.5 months (range 0-72). Age > 65 years, KPS ≤ 70, and CCI > 3 were significantly associated with both poor OS (each p < 0.0001) and PFS (p < 0.0001, p < 0.001 and p < 0.002), respectively. Also, patients older than 65 years significantly had a CCI > 3 (p < 0.0001).

CONCLUSIONS

Our data evidence that aside established prognostic parameters (age and KPS) for GB patient outcome, the CCI additionally significantly impacts outcome and may be employed for preoperative patient stratification.

Recognizing and correcting failures in glioblastoma treatment

While current treatment remains universal for glioblastoma, recent evidence has demonstrated marked heterogeneity in their molecular profiles. Due to the near universal rate of recurrence, attention has focused on individualized treatment and subgroup population differences that may influence the efficacy of adjuvant therapy. Recent studies have implicated chemo-radioresistant GBM stem cells (GSCs) in the propagation of heterogeneous tumor profiles. As a result, there has been a shift to classify and target GSCs in order to increase survival and delay relapse. The overall objective of our editorial is to highlight current failures in GBM treatment and to propose novel personalized methods to correct our shortcomings in GBM treatment.

Malignant gliomas: current perspectives in diagnosis, treatment, and early response assessment using advanced quantitative imaging methods

Malignant gliomas consist of glioblastomas, anaplastic astrocytomas, anaplastic oligodendrogliomas and anaplastic oligoastrocytomas, and some less common tumors such as anaplastic ependymomas and anaplastic gangliogliomas. Malignant gliomas have high morbidity and mortality. Even with optimal treatment, median survival is only 12–15 months for glioblastomas and 2–5 years for anaplastic gliomas. However, recent advances in imaging and quantitative analysis of image data have led to earlier diagnosis of tumors and tumor response to therapy, providing oncologists with a greater time window for therapy management. In addition, improved understanding of tumor biology, genetics, and resistance mechanisms has enhanced surgical techniques, chemotherapy methods, and radiotherapy administration. After proper diagnosis and institution of appropriate therapy, there is now a vital need for quantitative methods that can sensitively detect malignant glioma response to therapy at early follow-up times, when changes in management of nonresponders can have its greatest effect. Currently, response is largely evaluated by measuring magnetic resonance contrast and size change, but this approach does not take into account the key biologic steps that precede tumor size reduction. Molecular imaging is ideally suited to measuring early response by quantifying cellular metabolism, proliferation, and apoptosis, activities altered early in treatment. We expect that successful integration of quantitative imaging biomarker assessment into the early phase of clinical trials could provide a novel approach for testing new therapies, and importantly, for facilitating patient management, sparing patients from weeks or months of toxicity and ineffective treatment. This review will present an overview of epidemiology, molecular pathogenesis and current advances in diagnoses, and management of malignant gliomas.

Statistical and practical considerations for clinical evaluation of predictive biomarkers

Predictive biomarkers to guide therapy for cancer patients are a cornerstone of precision medicine. Discussed herein are considerations regarding the design and interpretation of such predictive biomarker studies. These considerations are important for both planning and interpreting prospective studies and for using specimens collected from completed randomized clinical trials. Specific issues addressed are differentiation between qualitative and quantitative predictive effects, challenges due to sample size requirements for predictive biomarker assessment, and consideration of additional factors relevant to clinical utility assessment, such as toxicity and cost of new therapies as well as costs and potential morbidities associated with routine use of biomarker-based tests.

Targeted therapy with bevacizumab and erlotinib tailored to the molecular profile of patients with recurrent glioblastoma. Preliminary experience

BACKGROUND

Advances in comprehension of molecular biology of glioblastoma (GBM) have led to the development of targeted therapies. The aim of the present study was to evaluate the efficacy and safety of a targeted therapeutic approach in which administration of bevacizumab and erlotinib was tailored on the molecular profile of recurrent GBM.

METHODS

We prospectively enrolled ten adult patients suffering from recurrent GBM who had undergone surgical resection and standard chemo-radiotherapy. Tumor tissue was assessed for the expression of EGFRvIII and MGMT promoter methylation by RT-PCR, and for PTEN and VEGF expression by immunohistochemistry. Normal PTEN status was required for inclusion. Patients with VEGF overexpressing tumors (10/10) were treated with bevacizumab (10 mg/kg iv every 2 weeks in 6-week cycles); patients whose tumor expressed EGFRvIII (4/10) added erlotinib (150 mg/day orally; 300 mg/day if on enzyme-inducing antiepileptic drugs). Therapy was continued until disease progression or unacceptable toxicity. Primary endpoints of the study were response rate (RR), 6-month progression-free survival (PFS-6), and safety profile.

RESULTS

The RR and PFS-6 were 100 % (4/4) and 50 % (3/6) in patients treated with bevacizumab+erlotinib (n = 4) and bevacizumab (n = 6), respectively. In the whole cohort (n = 10), RR and PFS-6 were both 70 % (7/10); median PFS and overall survival (OS) were 8.0 (3.0-31.0) and 9.5 (5.0-31.0) months, respectively. No grade 3/4 adverse events were observed; three patients treated with bevacizumab+erlotinib displayed grade 1/2 rash not requiring dose reduction; one patient treated with bevacizumab developed intratumoral hemorrhage requiring treatment discontinuation.

CONCLUSION

To our knowledge, this is the first study on recurrent GBM in which administration of bevacizumab and erlotinib was tailored on the molecular profile of the patient's tumor. Although we treated a limited number of patients, we obtained significantly higher RR and PFS-6 than those reported in a previous trial lacking molecular tumor analysis.

Standards of care for treatment of recurrent glioblastoma--are we there yet?

Newly diagnosed glioblastoma is now commonly treated with surgery, if feasible, or biopsy, followed by radiation plus concomitant and adjuvant temozolomide. The treatment of recurrent glioblastoma continues to be a moving target as new therapeutic principles enrich the standards of care for newly diagnosed disease. We reviewed PubMed and American Society of Clinical Oncology abstracts from January 2006 to January 2012 to identify clinical trials investigating the treatment of recurrent or progressive glioblastoma with nitrosoureas, temozolomide, bevacizumab, and/or combinations of these agents. At recurrence, a minority of patients are eligible for second surgery or reirradiation, based on appropriate patient selection. In temozolomide-pretreated patients, progression-free survival rates at 6 months of 20%-30% may be achieved either with nitrosoureas, temozolomide in various dosing regimens, or bevacizumab. Combination regimens among these agents or with other drugs have not produced evidence for superior activity but commonly produce more toxicity. More research is needed to better define patient profiles that predict benefit from the limited therapeutic options available after the current standard of care has failed.

Personalized medicine in neurosurgery

Personalized medicine (PM) in neurosurgery is possible today thanks to newly accessible imaging technologies, and to genomic, proteomic and epigenetic biomarkers capable of providing clinically useful information about individual patients. PM is becoming increasingly indispensable in neurosurgery because this specialty offers a wide range of therapeutic options such as surgery and/or radiotherapy and/or chemotherapy. Moreover, the effectiveness of these procedures varies from one patient to another, depending inter alia on the patients' individual genomic traits. A prime example is glioblastoma multiforme, which exhibits at least five genomic biomarkers related to distinct therapeutic and prognostic outcomes. At least one of these biomarkers, the ω-6 methylguanine-DNA methyltransferase promoter of methylation status, has already been used in clinical trials. New functional imaging techniques allow the surgeon to circumvent crucial brain areas whose location may vary among patients, thus allowing the safe and complete excision of an adjacent tumor. Functional imaging, together with an increasing number of genomic and other 'omic' biomarkers, has also given rise to an improved classification based on molecular signatures of tumors like glioblastoma multiforme that will facilitate the correspondence between type of glioma and choice of biologically tailored-to-patient therapy.

Review: molecular pathology in adult high-grade gliomas: from molecular diagnostics to target therapies

The classification of malignant gliomas is moving from a morphology-based guide to a system built on molecular criteria. The development of a genomic landscape for gliomas and a better understanding of its functional consequences have led to the development of internally consistent molecular classifiers. However, development of a biologically insightful classification to guide therapy is still a work in progress. Response to targeted treatments is based not only on the presence of drugable targets, but rather on the molecular circuitry of the cells. Further, tumours are heterogeneous and change and adapt in response to drugs. Therefore, the challenge of developing molecular classifiers that provide meaningful ways to stratify patients for therapy remains a major challenge for the field. In this review, we examine the potential role of MGMT methylation, IDH1/2 mutations, 1p/19q deletions, aberrant epidermal growth factor receptor and PI3K pathways, abnormal p53/Rb pathways, cancer stem-cell markers and microRNAs as prognostic and predictive molecular markers in the setting of adult high-grade gliomas and we outline the clinically relevant subtypes of glioblastoma with genomic, transcriptomic and proteomic integrated analyses. Furthermore, we describe how these advances, especially in epidermal growth factor receptor/PI3K/mTOR signalling pathway, affect our approaches towards targeted therapy, raising new challenges and identifying new leads.

Apparent diffusion coefficient histogram analysis stratifies progression-free and overall survival in patients with recurrent GBM treated with bevacizumab: a multi-center study

We have tested the predictive value of apparent diffusion coefficient (ADC) histogram analysis in stratifying progression-free survival (PFS) and overall survival (OS) in bevacizumab-treated patients with recurrent glioblastoma multiforme (GBM) from the multi-center BRAIN study. Available MRI's from patients enrolled in the BRAIN study (n = 97) were examined by generating ADC histograms from areas of enhancing tumor on T1 weighted post-contrast images fitted to a two normal distribution mixture curve. ADC classifiers including the mean ADC from the lower curve (ADC-L) and the mean lower curve proportion (LCP) were tested for their ability to stratify PFS and OS by using Cox proportional hazard ratios and the Kaplan-Meier method with log-rank test. Mean ADC-L was 1,209 × 10(-6)mm(2)/s ± 224 (SD), and mean LCP was 0.71 ± 0.23 (SD). Low ADC-L was associated with worse outcome. The hazard ratios for 6-month PFS, overall PFS, and OS in patients with less versus greater than mean ADC-L were 3.1 (95 % confidence interval: 1.6, 6.1; P = 0.001), 2.3 (95 % CI: 1.3, 4.0; P = 0.002), and 2.4 (95 % CI: 1.4, 4.2; P = 0.002), respectively. In patients with ADC-L <1,209 and LCP >0.71 versus ADC-L >1,209 and LCP <0.71, there was a 2.28-fold reduction in the median time to progression, and a 1.42-fold decrease in the median OS. The predictive value of ADC histogram analysis, in which low ADC-L was associated with poor outcome, was confirmed in bevacizumab-treated patients with recurrent GBM in a post hoc analysis from the multi-center (BRAIN) study.

A specific miRNA signature in the peripheral blood of glioblastoma patients

The prognosis of patients afflicted by glioblastoma remains poor. Biomarkers for the disease would be desirable in order to allow for an early detection of tumor progression or to indicate rapidly growing tumor subtypes requiring more intensive therapy. In this study, we investigated whether a blood-derived specific miRNA fingerprint can be defined in patients with glioblastoma. To this end, miRNA profiles from the blood of 20 patients with glioblastoma and 20 age- and sex-matched healthy controls were compared. Of 1158 tested miRNAs, 52 were significantly deregulated, as assessed by unadjusted Student's t-test at an alpha level of 0.05. Of these, two candidates, miR-128 (up-regulated) and miR-342-3p (down-regulated), remained significant after correcting for multiple testing by Benjamini-Hochberg adjustment with a p-value of 0.025. The altered expression of these two biomarkers was confirmed in a second cohort of glioblastoma patients and healthy controls by real-time PCR and validated for patients who had received neither radio- nor chemotherapy and for patients who had their glioblastomas resected more than 6 months ago. Moreover, using machine learning, a comprehensive miRNA signature was obtained that allowed for the discrimination between blood samples of glioblastoma patients and healthy controls with an accuracy of 81% [95% confidence interval (CI) 78-84%], specificity of 79% (95% CI 75-83%) and sensitivity of 83% (95% CI 71-85%). In summary, our proof-of-concept study demonstrates that blood-derived glioblastoma-associated characteristic miRNA fingerprints may be suitable biomarkers and warrant further exploration.