Outcome of Bevacizumab Therapy in Patients with Recurrent Glioblastoma Treated with Angiotensin System Inhibitors.

PURPOSE: Antihypertensive therapy may improve bevacizumab efficacy in cancer patients. We examined efficacy and toxicity of angiotensin system inhibitors (ASI) and other antihypertensive drugs in bevacizumab treated recurrent glioblastoma patients. METHODS: We retrospectively combined a national prescription registry with a clinical database with recurrent glioblastoma patients (n = 243). RESULTS: Patients who initiated ASI after bevacizumab (n = 26) showed a tendency towards improved progression-free survival and overall survival (OS) with hazard rate (HR) reductions (HR = 0.70 and HR = 0.79, respectively). Calcium antagonists during bevacizumab therapy significantly improved OS (HR = 0.57). CONCLUSIONS: Overall the study supports a potential beneficial effect of antihypertensive treatment on prognosis of bevacizumab treated glioblastoma patients.

Biomarkers in Recurrent Grade III Glioma Patients Treated with Bevacizumab and Irinotecan.

Predictive biomarkers and prognostic models are required to identify recurrent grade III glioma patients who benefit from existing treatment. In this study of 62 recurrent grade III glioma patients, a range of clinical and paraclinical factors are tested for association with progression-free survival, overall survival, and response to bevacizumab and irinotecan therapy. Significant factors from univariate screening are included in multivariate analysis. Biomarkers previously advanced as predictive or prognostic in the first-line setting did not affect outcome in this patient cohort. Based on the optimized model for overall survival, comprising performance status and p53 expression, a prognostic index is established.

Molecular profiling of short-term and long-term surviving patients identifies CD34 mRNA level as prognostic for glioblastoma survival.

Despite extensive treatment, overall survival (OS) for glioblastoma (GBM) remains poor. A small proportion of patients present long survival over 3 years, but the underlying molecular background separating these long-term survivors (LTS) from short-term survivors (STS) are insufficiently understood. Accordingly, study aim was to identify independent prognostic biomarkers for survival. Study cohort consisted of 93 primary GBM patients treated with radiation-, chemo- and bevacizumab therapy, among which 14 STS (OS ≤ 12 months) and 6 LTS (OS ≥ 36 months) were identified, all confirmed being IDH wild-type. RNA expression levels in diagnostic tumor specimen for 792 genes were analyzed by NanoString technology. While no differences were found with regard to GBM subtype between LTS versus STS, comparative analysis of individual genes identified 14 significantly differently expressed candidate genes. Univariate analysis in the whole patient cohort found that 12 of these were significantly associated with OS, of which increased IFNG, CXCL9, LGALS4, CD34 and decreased MGMT levels remained significant associated with prolonged OS in multivariate analysis correcting for known prognostic variables. Validation analyses in an independent dataset from the AVAglio study confirmed CD34 as significant in comparative analysis between STS and LTS patients and as an independent prognostic factor. Analysis of this dataset further supported CD34 expression to be associated with improved bevacizumab efficacy, while CD34 immunohistochemistry indicated variation in CD34 expression to result primarily from varying tumor vascularization. Collectively, CD34 expression candidates as a prognostic biomarker in GBM able to identify survival outliers and could also be predictive for efficacy of bevacizumab.

DNA Methylation Levels of the ELMO Gene Promoter CpG Islands in Human Glioblastomas.

Complete surgical resection of glioblastoma is difficult due to the invasive nature of this primary brain tumor, for which the molecular mechanisms behind remain poorly understood. The three human ELMO genes play key roles in cellular motility, and have been linked to metastasis and poor prognosis in other cancer types. The aim of this study was to investigate methylation levels of the ELMO genes and their correlation to clinical characteristics and outcome in patients diagnosed with glioblastoma. To measure DNA methylation levels we designed pyrosequencing assays targeting the promoter CpG island of each the ELMO genes. These were applied to diagnostic tumor specimens from a well-characterized cohort of 121 patients who received standard treatment consisting of surgery, radiation therapy, plus concomitant and adjuvant chemotherapy. The promoter methylation levels of ELMO1 and ELMO2 were generally low, whereas ELMO3 methylation levels were high, in the tumor biopsies. Thirteen, six, and 18 biopsies were defined as aberrantly methylated for ELMO1, ELMO2, and ELMO3, respectively. There were no significant associations between the methylation status of any of the ELMO gene promoter CpG islands and overall survival, progression-free survival, and clinical characteristics of the patients including intracranial tumor location. Therefore, the methylation status of the ELMO gene promoter CpG islands is unlikely to have prognostic value in glioblastoma.

The prognostic value of FET PET at radiotherapy planning in newly diagnosed glioblastoma.

BACKGROUND: Glioblastoma patients show a great variability in progression free survival (PFS) and overall survival (OS). To gain additional pretherapeutic information, we explored the potential of O-(2-18F-fluoroethyl)-L-tyrosine (FET) PET as an independent prognostic biomarker. METHODS: We retrospectively analyzed 146 consecutively treated, newly diagnosed glioblastoma patients. All patients were treated with temozolomide and radiation therapy (RT). CT/MR and FET PET scans were obtained postoperatively for RT planning. We used Cox proportional hazards models with OS and PFS as endpoints, to test the prognostic value of FET PET biological tumor volume (BTV). RESULTS: Median follow-up time was 14 months, and median OS and PFS were 16.5 and 6.5 months, respectively. In the multivariate analysis, increasing BTV (HR = 1.17, P < 0.001), poor performance status (HR = 2.35, P < 0.001), O(6)-methylguanine-DNA methyltransferase protein status (HR = 1.61, P = 0.024) and higher age (HR = 1.32, P = 0.013) were independent prognostic factors of poor OS. For poor PFS, only increasing BTV (HR = 1.18; P = 0.002) was prognostic. A prognostic index for OS was created based on the identified prognostic factors. CONCLUSION: Large BTV on FET PET is an independent prognostic factor of poor OS and PFS in glioblastoma patients. With the introduction of FET PET, we obtain a prognostic index that can help in glioblastoma treatment planning.

Transcriptional changes induced by bevacizumab combination therapy in responding and non-responding recurrent glioblastoma patients.

BACKGROUND: Bevacizumab combined with chemotherapy produces clinical durable response in 25-30% of recurrent glioblastoma patients. This group of patients has shown improved survival and quality of life. The aim of this study was to investigate changes in gene expression associated with response and resistance to bevacizumab combination therapy. METHODS: Recurrent glioblastoma patients who had biomarker-accessible tumor tissue surgically removed both before bevacizumab treatment and at time of progression were included. Patients were grouped into responders (n = 7) and non-responders (n = 14). Gene expression profiling of formalin-fixed paraffin-embedded tumor tissue was performed using RNA-sequencing. RESULTS: By comparing pretreatment samples of responders with those of non-responders no significant difference was observed. In a paired comparison analysis of pre- and posttreatment samples of non-responders 1 gene was significantly differentially expressed. In responders, this approach revealed 256 significantly differentially expressed genes (72 down- and 184 up-regulated genes at the time of progression). Genes differentially expressed in responders revealed a shift towards a more proneural and less mesenchymal phenotype at the time of progression. CONCLUSIONS: Bevacizumab combination treatment demonstrated a significant impact on the transcriptional changes in responders; but only minimal changes in non-responders. This suggests that non-responding glioblastomas progress chaotically without following distinct gene expression changes while responding tumors adaptively respond or progress by means of the same transcriptional changes. In conclusion, we hypothesize that the identified gene expression changes of responding tumors are associated to bevacizumab response or resistance mechanisms.

Development and validation of a prognostic model for recurrent glioblastoma patients treated with bevacizumab and irinotecan.

BACKGROUND: Predictive markers and prognostic models are required in order to individualize treatment of recurrent glioblastoma (GBM) patients. Here, we sought to identify clinical factors able to predict response and survival in recurrent GBM patients treated with bevacizumab (BEV) and irinotecan. MATERIAL AND METHODS: A total of 219 recurrent GBM patients treated with BEV plus irinotecan according to a previously published treatment protocol were included in the initial population. Prognostic models were generated by means of multivariate logistic and Cox regression analysis. RESULTS: In multivariate analysis, corticosteroid use had a negative predictive impact on response at first evaluation (OR 0.45; 95% CI 0.22-0.93; p = 0.03) and at best response (OR 0.51; 95% CI 0.26-1.02; p = 0.056). Three significant (p < 0.05) prognostic factors associated with reduced progression-free survival and overall survival (OS) were identified. These factors were included in the final model for OS, namely corticosteroid use (HR 1.70; 95% CI 1.18-2.45; p = 0.004), neurocognitive deficit (HR 1.40; 95% CI 1.04-1.89; p = 0.03) and multifocal disease (HR 1.56; 95% CI 1.15-2.11; p < 0.0001). Based on these results a prognostic index able to calculate the probability for OS at 6 and 12 months for the individual patient was established. The predictive value of the model for OS was validated in a separate patient cohort of 85 patients. DISCUSSION AND CONCLUSION: A prognostic model for OS was established and validated. This model can be used by physicians to risk stratify the individual patient and together with the patient decide whether to initiate BEV relapse treatment.

Prognostic relevance of radiological findings on early postoperative MRI for 187 consecutive glioblastoma patients receiving standard therapy.

Several prognostic factors are known to influence survival for patients treated with IDH-wildtype glioblastoma, but unknown factors may remain. We aimed to investigate the prognostic implications of early postoperative MRI findings. A total of 187 glioblastoma patients treated with standard therapy were consecutively included. Patients either underwent a biopsy or surgery followed by an early postoperative MRI. Progression-free survival (PFS) and overall survival (OS) were analysed for known prognostic factors and MRI-derived candidate factors: resection status as defined by the response assessment in neuro-oncology (RANO)-working group (no contrast-enhancing residual tumour, non-measurable contrast-enhancing residual tumour, or measurable contrast-enhancing residual tumour) with biopsy as reference, contrast enhancement patterns (no enhancement, thin linear, thick linear, diffuse, nodular), and the presence of distant tumours. In the multivariate analysis, patients with no contrast-enhancing residual tumour or non-measurable contrast-enhancing residual tumour on the early postoperative MRI displayed a significantly improved progression-free survival compared with patients receiving only a biopsy. Only patients with non-measurable contrast-enhancing residual tumour showed improved overall survival in the multivariate analysis. Contrast enhancement patterns were not associated with survival. The presence of distant tumours was significantly associated with both poor progression-free survival and overall survival and should be considered incorporated into prognostic models.

A systematic review of targeted therapy for vestibular schwannoma in patients with NF2-related schwannomatosis.

Background: One of the hallmarks of NF2-related Schwannomatosis (NF2-related SWN) is bilateral vestibular schwannomas (VS) that can cause progressive hearing impairment in patients. This systematic review was performed to investigate the efficacy and toxicity of tested targeted agents. Methods: The systematic search was conducted on PubMed and EMBASE Ovid databases from inception to October 2022, according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The incidence of outcomes in studies involving bevacizumab and other targeted therapies was extracted. The bevacizumab results were pooled, and 95% confidence intervals (95% CI) were calculated. Results: Sixteen studies (8 prospective and 8 retrospective) testing 6 drugs were selected out of 721 search results. There were 10 studies concerning bevacizumab, with a total of 200 patients. The pooled radiographic response rate (RR) was 38% (95% CI: 31 - 45%) and the pooled hearing response rate (HR) was 45% (95% CI: 36 - 54%). The most frequent bevacizumab-related toxicities were hypertension and menorrhagia. Of other targeted therapies showing activity, lapatinib had a RR of 6% and a HR of 31%. A VEGFR vaccine showed RR in 29% and HR in 40% of patients. Both agents had a manageable safety profile. Conclusions: Bevacizumab, in comparison to other targeted agents, showed the highest efficacy. Lower dosage of bevacizumab shows comparable efficacy and may reduce toxicity. Other targeted agents, administered alone or as combination therapy, have the potential to improve outcomes for VS in patients with NF2-related SWN, but future clinical studies are needed.

The Neurogenome study: Comprehensive molecular profiling to optimize treatment for Danish glioblastoma patients.

Background: Glioblastoma is an aggressive brain cancer with no possibility for cure. Treatment and survival have only improved slightly since 2005 when the current regime was implemented. The limited improvements in the treatment of glioblastoma may reflect our poor understanding of the disease. We hypothesize that systematically collected translational data will improve knowledge and hereby treatment. Methods: We have been performing whole exome sequencing in glioblastoma tumor tissue since 2016 and whole genome sequencing (WGS) since 2020 with the aim of offering experimental treatment. Results: We have sequenced 400+ GBM patients and from these 100+ are paired tumor samples from relapse surgery. To develop genomic profiling and to increase the information on each patient´s contribution, we have initiated the Neurogenome study as of June 2022. The Neurogenome protocol is a national, comprehensive, translational, and omic protocol. It is a continuation of 2 previous protocols from 2016 and forth in our department, but with more substudies added, focusing on the translational and clinical utility. We collect and analyze data from an out-patient clinic in a systematic approach to a number of subprojects ranging from basic science to applied clinical science, including clinical trials. Conclusions: The protocol will act as a backbone for future projects in the national research center, Danish Comprehensive Cancer Center-Brain Tumor Center with the overall aim to select eligible patients for experimental treatment based upon genomic alterations. The article will present the Neurogenome setup and a presentation of selected projects that are based upon inclusion.

Implementing targeted therapies in the treatment of glioblastoma: Previous shortcomings, future promises, and a multimodal strategy recommendation.

The introduction of targeted therapies to the field of oncology has prolonged the survival of several tumor types. Despite extensive research and numerous trials, similar outcomes have unfortunately not been realized for glioblastoma. For more than 15 years, the standard treatment of glioblastoma has been unchanged. This review walks through the elements that have challenged the success of previous trials and highlight some future promises. Concurrently, this review describes how institutions, through a multimodal and comprehensive strategy with 4 essential components, may increase the probability of finding a meaningful role for targeted therapies in the treatment of glioblastoma. These components are (1) prudent trial designs, (2) considered drug and target selection, (3) harnessed real-world clinical and molecular evidence, and (4) incorporation of translational research.

Predicting survival of glioblastoma from automatic whole-brain and tumor segmentation of MR images.

Survival prediction models can potentially be used to guide treatment of glioblastoma patients. However, currently available MR imaging biomarkers holding prognostic information are often challenging to interpret, have difficulties generalizing across data acquisitions, or are only applicable to pre-operative MR data. In this paper we aim to address these issues by introducing novel imaging features that can be automatically computed from MR images and fed into machine learning models to predict patient survival. The features we propose have a direct anatomical-functional interpretation: They measure the deformation caused by the tumor on the surrounding brain structures, comparing the shape of various structures in the patient's brain to their expected shape in healthy individuals. To obtain the required segmentations, we use an automatic method that is contrast-adaptive and robust to missing modalities, making the features generalizable across scanners and imaging protocols. Since the features we propose do not depend on characteristics of the tumor region itself, they are also applicable to post-operative images, which have been much less studied in the context of survival prediction. Using experiments involving both pre- and post-operative data, we show that the proposed features carry prognostic value in terms of overall- and progression-free survival, over and above that of conventional non-imaging features.

A Prognostic Model for Glioblastoma Patients Treated With Standard Therapy Based on a Prospective Cohort of Consecutive Non-Selected Patients From a Single Institution.

BACKGROUND: Glioblastoma patients administered standard therapies, comprising maximal surgical resection, radiation therapy with concomitant and adjuvant temozolomide, have a variable prognosis with a median overall survival of 15-16 months and a 2-year overall survival of 30%. The aim of this study was to develop a prognostic nomogram for overall survival for glioblastoma patients treated with standard therapy outside clinical trials. METHODS: The study included 680 consecutive, non-selected glioblastoma patients administered standard therapy as primary treatment between the years 2005 and 2016 at Rigshospitalet, Copenhagen, Denmark. The prognostic model was generated employing multivariate Cox regression analysis modeling overall survival. RESULTS: The following poor prognostic factors were included in the final prognostic model for overall survival: Age (10-year increase: HR = 1.18, 95% CI: 1.08-1.28, p < 0.001), ECOG performance status (PS) 1 vs. 0 (HR = 1.30, 95% CI: 1.07-1.57, p = 0.007), PS 2 vs. 0 (HR = 2.99, 95% CI: 1.99-4.50, p < 0.001), corticosteroid use (HR = 1.42, 95% CI: 1.18-1.70, p < 0.001), multifocal disease (HR = 1.63, 95% CI: 1.25-2.13, p < 0.001), biopsy vs. resection (HR = 1.35, 95% CI: 1.04-1.72, p = 0.02), un-methylated promoter of the MGMT (O6-methylguanine-DNA methyltransferase) gene (HR = 1.71, 95% CI: 1.42-2.04, p < 0.001). The model was validated internally and had a concordance index of 0.65. CONCLUSION: A nomogram for overall survival was established. This model can be used for risk stratification and treatment planning, as well as improve enrollment criteria for clinical trials.

Angiotensinogen promoter methylation predicts bevacizumab treatment response of patients with recurrent glioblastoma.

Patients with recurrent glioblastoma achieving response to bevacizumab combined with chemotherapy have clinical improvement and prolonged survival. High gene expression of angiotensinogen (AGT) is associated with a poor bevacizumab response. Because AGT expression is epigenetically regulated, we aimed to investigate whether AGT promoter methylation in tumor tissue predicts response to bevacizumab combination therapy in patients with recurrent glioblastoma. The study included 159 patients with recurrent glioblastoma, treated with bevacizumab combination treatment (training cohort, n = 77; validation cohort, n = 82). All patients could be evaluated for treatment response and biomarkers. DNA methylation of 4 CpG sites in the AGT promoter was measured using pyrosequencing. A model for nonresponse was established using logistic regression analysis. In the training cohort, lower methylation of each of the four CpG sites in the AGT promoter was significantly associated with nonresponse (all P < 0.05). Moreover, the mean methylation level of all four CpG sites was associated with an increased likelihood of not achieving response to bevacizumab combination therapy (twofold decrease: odds ratio = 3.01; 95% confidence interval: 1.41-6.44; P = 0.004). We developed a model for nonresponse in the training cohort, where a threshold of mean AGT promoter methylation levels was set to below 12%. The model could predict bevacizumab nonresponse with 96% specificity. Importantly, this predictor was also significantly associated with nonresponse in the validation cohort (P = 0.037). Taken together, our findings suggest that low AGT promoter methylation in tumor tissue predicts nonresponse to bevacizumab combination treatment in patients with recurrent glioblastoma. We have, thus, established and successfully validated a predictor for nonresponse that can be used to identify patients who will not benefit from bevacizumab combination therapy.

Recurrent glioblastoma versus late posttreatment changes: diagnostic accuracy of O-(2-[18F]fluoroethyl)-L-tyrosine positron emission tomography (18F-FET PET).

BACKGROUND: Diagnostic accuracy in previous studies of O-(2-[18F]-fluoroethyl)-L-tyrosine (18F-FET) PET in patients with suspected recurrent glioma may be influenced by prolonged dynamic PET acquisitions, heterogeneous populations, different non-standard-of-care therapies, and PET scans performed at different time points post radiotherapy. We investigated the diagnostic accuracy of a 20-minute 18F-FET PET scan in MRI-suspected recurrent glioblastoma 6 months after standard radiotherapy and its ability to prognosticate overall survival (OS). METHODS: In total, 146 glioblastoma patients with 168 18F-FET PET scans were reviewed retrospectively. Patients with MRI responses to bevacizumab or undergoing re-irradiation or immunotherapy after 18F-FET PET were excluded. Maximum and mean tumor-to-background ratios (TBRmax, TBRmean) and biological tumor volume (BTV) were recorded and verified by histopathology or clinical/radiological follow-up. Thresholds of 18F-FET parameters were determined by receiver operating characteristic (ROC) analysis. Prognostic factors were investigated in Cox proportional hazards models. RESULTS: Surgery was performed after 104 18F-FET PET scans, while clinical/radiological surveillance was used following 64, identifying 152 glioblastoma recurrences and 16 posttreatment changes. ROC analysis yielded thresholds of 2.0 for TBRmax, 1.8 for TBRmean, and 0.55 cm3 for BTV in differentiating recurrent glioblastoma from posttreatment changes with the best performance of TBRmax (sensitivity 99%, specificity 94%; P < 0.0001) followed by BTV (sensitivity 98%, specificity 94%; P < 0.0001). Using these thresholds, 166 18F-FET PET scans were correctly classified. Increasing BTV was associated with shorter OS (P < 0.0001). CONCLUSION: A 20-minute 18F-FET PET scan is a powerful tool to distinguish posttreatment changes from recurrent glioblastoma 6-month postradiotherapy, and predicts OS.

VEGF-C sustains VEGFR2 activation under bevacizumab therapy and promotes glioblastoma maintenance.

Background: Glioblastoma ranks among the most lethal cancers, with current therapies offering only palliation. Paracrine vascular endothelial growth factor (VEGF) signaling has been targeted using anti-angiogenic agents, whereas autocrine VEGF/VEGF receptor 2 (VEGFR2) signaling is poorly understood. Bevacizumab resistance of VEGFR2-expressing glioblastoma cells prompted interrogation of autocrine VEGF-C/VEGFR2 signaling in glioblastoma. Methods: Autocrine VEGF-C/VEGFR2 signaling was functionally investigated using RNA interference and exogenous ligands in patient-derived xenograft lines and primary glioblastoma cell cultures in vitro and in vivo. VEGF-C expression and interaction with VEGFR2 in a matched pre- and post-bevacizumab treatment cohort were analyzed by immunohistochemistry and proximity ligation assay. Results: VEGF-C was expressed by patient-derived xenograft glioblastoma lines, primary cells, and matched surgical specimens before and after bevacizumab treatment. VEGF-C activated autocrine VEGFR2 signaling to promote cell survival, whereas targeting VEGF-C expression reprogrammed cellular transcription to attenuate survival and cell cycle progression. Supporting potential translational significance, targeting VEGF-C impaired tumor growth in vivo, with superiority to bevacizumab treatment. Conclusions: Our results demonstrate VEGF-C serves as both a paracrine and an autocrine pro-survival cytokine in glioblastoma, promoting tumor cell survival and tumorigenesis. VEGF-C permits sustained VEGFR2 activation and tumor growth, where its inhibition appears superior to bevacizumab therapy in improving tumor control.

Angiotensinogen and HLA class II predict bevacizumab response in recurrent glioblastoma patients.

BACKGROUND: Bevacizumab combination therapy is among the most frequently used treatments in recurrent glioblastoma and patients who achieve response to bevacizumab have improved survival as well as quality of life. Accordingly, the aim of this study was to identify predictive biomarkers for bevacizumab response in recurrent glioblastoma patients. METHODS: The study included a total of 82 recurrent glioblastoma patients treated with bevacizumab combination therapy whom were both response and biomarker evaluable. Gene expression of tumor tissue was analyzed by using a customized NanoString platform covering 800 genes. Candidate gene predictors associated with response were analyzed by multivariate logistic and Cox regression analysis. RESULTS: Two genes were independently associated with response: Low expression of angiotensinogen (2-fold decrease in AGT; OR = 2.44; 95% CI: 1.45-4.17; P = 0.0009) and high expression of a HLA class II gene (2-fold increase in HLA-DQA1; OR = 1.22; 95% CI: 1.01-1.47; P = 0.04). These two genes were included in a model that is able predict response to bevacizumab combination therapy in clinical practice. When stratified for a validated prognostic index, the predictive model for response was significantly associated with improved overall survival. CONCLUSION: Two genes (low angiotensinogen and high HLA-class II expression) were predictive for bevacizumab response and were included in a predictive model for response. This model can be used in clinical practice to identify patients who will benefit from bevacizumab combination therapy.

Characterization of memory B cells from thymus and its impact for DLBCL classification.

The rare memory B cells in thymus (Thy) are considered the cells of origin for primary mediastinal large B-cell lymphoma. The objectives of the present study were to characterize the normal memory B-cell compartment in Thy and to support its association with primary mediastinal B-cell lymphoma. Seven paired human tissue samples from Thy and sternum bone marrow (BM) were harvested during cardiac surgery. B-cell subsets were phenotyped by Euroflow standard and fluorescence-activated cell sorting for microarray analysis on the Human Exon 1.0 ST Arrays platform. Differentially expressed genes between Thy and BM memory B cells were identified and correlated with the molecular subclasses of diffuse large B-cell lymphoma. Within Thy, 4% (median; range 2%-14%) of the CD45(+) hematopoietic cells were CD19(+) B cells, with a major fraction being CD27(+)/CD38(-) memory B cells (median 80%, range 76%-93%). The BM contained 14% (median; range 3%-27%), of which only a minor fraction (median 5%, range 2%-10%) were memory B cells. Global gene expression analysis of the memory B-cell subsets from the two compartments identified 133 genes upregulated in Thy, including AICDA, REL, STAT1, TNF family, SLAMF1, CD80, and CD86. In addition, exons 4 and 5 in the 3' end of AICDA were more highly expressed in Thy than in BM. The Thy memory B-cell gene profile was overexpressed in primary mediastinal B-cell lymphoma compared with other diffuse large B-cell lymphoma subclasses. The present study describes a Thy memory B-cell subset and its gene profile correlated with primary mediastinal B-cell lymphomas, suggesting origin from Thy memory B cells.

18F-FET microPET and microMRI for anti-VEGF and anti-PlGF response assessment in an orthotopic murine model of human glioblastoma.

BACKGROUND: Conflicting data exist for anti-cancer effects of anti-placental growth factor (anti-PlGF) in combination with anti-VEGF. Still, this treatment combination has not been evaluated in intracranial glioblastoma (GBM) xenografts. In clinical studies, position emission tomography (PET) using the radiolabeled amino acid O-(2-18F-fluoroethyl)-L-tyrosine (18F-FET) and magnetic resonance imaging (MRI) add complementary but distinct information about glioma growth; however, the value of 18F-FET MicroPET combined with MicroMRI has not been investigated preclinically. Here we examined the use of 18F-FET MicroPET and MicroMRI for evaluation of anti-VEGF and anti-PlGF treatment response in GBM xenografts. METHODS: Mice with intracranial GBM were treated with anti-VEGF, anti-PlGF + anti-VEGF or saline. Bioluminescence imaging (BLI), 18F-FET MicroPET and T2-weighted (T2w)-MRI were used to follow tumour development. Primary end-point was survival, and tumours were subsequently analysed for Ki67 proliferation index and micro-vessel density (MVD). Further, PlGF and VEGFR-1 expression were examined in a subset of the xenograft tumours and in 13 GBM patient tumours. RESULTS: Anti-VEGF monotherapy increased survival and decreased 18F-FET uptake, BLI and MVD, while no additive effect of anti-PlGF was observed. 18F-FET SUV max tumour-to-brain (T/B) ratio was significantly lower after one week (114 ± 6%, n = 11 vs. 143 ± 8%, n = 13; p = 0.02) and two weeks of treatment (116 ± 12%, n = 8 vs. 190 ± 24%, n = 5; p = 0.02) in the anti-VEGF group as compared with the control group. In contrast, T2w-MRI volume was unaffected by anti-VEGF. Gene expression of PlGF and VEGFR-1 in xenografts was significantly lower than in patient tumours. CONCLUSION: 18F-FET PET was feasible for anti-angiogenic response evaluation and superior to T2w-MRI; however, no additive anti-cancer effect of anti-PlGF and anti-VEGF was observed. Thus, this study supports use of 18F-FET PET for response evaluation in future studies.

The impact of bevacizumab treatment on survival and quality of life in newly diagnosed glioblastoma patients.

Glioblastoma multiforme (GBM) remains one of the most devastating tumors, and patients have a median survival of 15 months despite aggressive local and systemic therapy, including maximal surgical resection, radiation therapy, and concomitant and adjuvant temozolomide. The purpose of antineoplastic treatment is therefore to prolong life, with a maintenance or improvement of quality of life. GBM is a highly vascular tumor and overexpresses the vascular endothelial growth factor A, which promotes angiogenesis. Preclinical data have suggested that anti-angiogenic treatment efficiently inhibits tumor growth. Bevacizumab is a humanized monoclonal antibody against vascular endothelial growth factor A, and treatment has shown impressive response rates in recurrent GBM. In addition, it has been shown that response is correlated to prolonged survival and improved quality of life. Several investigations in newly diagnosed GBM patients have been performed during recent years to test the hypothesis that newly diagnosed GBM patients should be treated with standard multimodality treatment, in combination with bevacizumab, in order to prolong life and maintain or improve quality of life. The results of these studies along with relevant preclinical data will be described, and pitfalls in clinical and paraclinical endpoints will be discussed.