Assessment of Ki-67 expression levels in IDH-wildtype glioblastoma using logistic regression modelling of VASARI features.

To investigate the value of using VASARI signs preoperatively to assess Ki-67 proliferation index levels in patients with IDH-wildtype glioblastoma (GB).Pathological and imaging data of 154 patients with GB confirmed by surgical pathology were retrospectively analysed, and the level of Ki-67 proliferative index was assessed in tumour tissue samples from patients using immunohistochemistry (IHC) staining. Patients were divided into a high and low Ki-67 proliferation index expression group. Two radiologists analysed MRI images of patients with IDH-wildtype GB using the VASARI features system. VASARI parameters between the two groups were statistically analysed to identify characteristic parameters with significant differences and their predictive performance was determined using ROC curves.Among the obtained clinical and VASARI features of IDH-wildtype GB patients, the distribution of Maximum diameter, Proportion of necrosis and Hemorrhage was significantly different between the two groups (all p < 0.05). Multivariate logistic regression analysis showed that Maximum diameter and Hemorrhage were independent risk factors distinguishing the group with high and low expression of Ki-67 proliferative index. ROC curve analysis showed that the logistic regression model achieved an AUC value of 0.730 (95% CI: 0.639, 0.822), sensitivity of 0.628 and specificity of 0.756.Logistic regression modelling of preoperative VASARI features can be used as a reliable tool for predicting the level of Ki-67 proliferative index in IDH-wildtype GB patients, which can help in preoperative development of treatment and follow-up strategies for patients.

Identification of circulating miRNA as early diagnostic molecular markers in malignant glioblastoma base on decision tree joint scoring algorithm.

PURPOSE: The lack of clinical markers prevents early diagnosis of glioblastoma (GBM). Many studies have found that circulating microRNAs (miRNAs) can be used as early diagnostic markers of malignant tumours. Therefore, the identification of novel circulating miRNA biomolecular markers could be beneficial to clinicians in the early diagnosis of GBM. METHODS: We developed a decision tree joint scoring algorithm (DTSA), systematically integrating significance analysis of microarray (SAM), Pearson hierarchical clustering, T test, Decision tree and Entropy weight score algorithm, to screen out circulating miRNA molecular markers with high sensitivity and accuracy for early diagnosis of GBM. RESULTS: DTSA was developed and applied for GBM datasets and three circulating miRNA molecular markers were identified, namely, hsa-miR-2278, hsa-miR-555 and hsa-miR-892b. We have found that hsa-miR-2278 and hsa-miR-892b regulate the GBM pathway through target genes, promoting the development of GBM and affecting the survival of patients. DTSA has better classification effect in all data sets than other classification algorithms, and identified miRNAs are better than existing markers of GBM. CONCLUSION: These results suggest that DTSA can effectively identify circulating miRNA, thus contributing to the early diagnosis and personalised treatment of GBM.

Deep Learning Radiomics for the Assessment of Telomerase Reverse Transcriptase Promoter Mutation Status in Patients With Glioblastoma Using Multiparametric MRI.

BACKGROUND: Studies have shown that magnetic resonance imaging (MRI)-based deep learning radiomics (DLR) has the potential to assess glioma grade; however, its role in predicting telomerase reverse transcriptase (TERT) promoter mutation status in patients with glioblastoma (GBM) remains unclear. PURPOSE: To evaluate the value of deep learning (DL) in multiparametric MRI-based radiomics in identifying TERT promoter mutations in patients with GBM preoperatively. STUDY TYPE: Retrospective. POPULATION: A total of 274 patients with isocitrate dehydrogenase-wildtype GBM were included in the study. The training and external validation cohorts included 156 (54.3 ± 12.7 years; 96 males) and 118 (54 .2 ± 13.4 years; 73 males) patients, respectively. FIELD STRENGTH/SEQUENCE: Axial contrast-enhanced T1-weighted spin-echo inversion recovery sequence (T1CE), T1-weighted spin-echo inversion recovery sequence (T1WI), and T2-weighted spin-echo inversion recovery sequence (T2WI) on 1.5-T and 3.0-T scanners were used in this study. ASSESSMENT: Overall tumor area regions (the tumor core and edema) were segmented, and the radiomics and DL features were extracted from preprocessed multiparameter preoperative brain MRI images-T1WI, T1CE, and T2WI. A model based on the DLR signature, clinical signature, and clinical DLR (CDLR) nomogram was developed and validated to identify TERT promoter mutation status. STATISTICAL TESTS: The Mann-Whitney U test, Pearson test, least absolute shrinkage and selection operator, and logistic regression analysis were applied for feature selection and construction of radiomics and DL signatures. Results were considered statistically significant at P-value <0.05. RESULTS: The DLR signature showed the best discriminative power for predicting TERT promoter mutations, yielding an AUC of 0.990 and 0.890 in the training and external validation cohorts, respectively. Furthermore, the DLR signature outperformed CDLR nomogram (P = 0.670) and significantly outperformed clinical models in the validation cohort. DATA CONCLUSION: The multiparameter MRI-based DLR signature exhibited a promising performance for the assessment of TERT promoter mutations in patients with GBM, which could provide information for individualized treatment. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

ToMExO: A probabilistic tree-structured model for cancer progression.

Identifying the interrelations among cancer driver genes and the patterns in which the driver genes get mutated is critical for understanding cancer. In this paper, we study cross-sectional data from cohorts of tumors to identify the cancer-type (or subtype) specific process in which the cancer driver genes accumulate critical mutations. We model this mutation accumulation process using a tree, where each node includes a driver gene or a set of driver genes. A mutation in each node enables its children to have a chance of mutating. This model simultaneously explains the mutual exclusivity patterns observed in mutations in specific cancer genes (by its nodes) and the temporal order of events (by its edges). We introduce a computationally efficient dynamic programming procedure for calculating the likelihood of our noisy datasets and use it to build our Markov Chain Monte Carlo (MCMC) inference algorithm, ToMExO. Together with a set of engineered MCMC moves, our fast likelihood calculations enable us to work with datasets with hundreds of genes and thousands of tumors, which cannot be dealt with using available cancer progression analysis methods. We demonstrate our method's performance on several synthetic datasets covering various scenarios for cancer progression dynamics. Then, a comparison against two state-of-the-art methods on a moderate-size biological dataset shows the merits of our algorithm in identifying significant and valid patterns. Finally, we present our analyses of several large biological datasets, including colorectal cancer, glioblastoma, and pancreatic cancer. In all the analyses, we validate the results using a set of method-independent metrics testing the causality and significance of the relations identified by ToMExO or competing methods.

Nomograms for prognostic risk assessment in glioblastoma multiforme: Applications and limitations.

Glioblastoma multiforme (GBM) is the most common and aggressive form of brain cancer. Prognosis evaluation is of great significance in guiding individualized treatment and monitoring of GBM. By integrating different prognostic variables, nomograms simplify the statistical risk prediction model into numerical estimates for death or recurrence, and are hence widely applied in prognosis prediction. In the past two decades, the application of high-throughput profiling technology and the establishment of TCGA database and other public data deposits have provided opportunities to identify cancer-related molecules and prognostic biomarkers. As a result, both molecular features and clinical characteristics of cancer have been reported to be the key factors in nomogram model construction. This article comprehensively reviewed 35 studies of GBM nomograms, analyzed the present situation of GBM nomograms, and discussed the role and significance of nomograms in personalized risk assessment and clinical treatment decision-making. To facilitate the application of nomograms in the prognostic prediction of GBM patients, a website has been established for the online access of nomograms based on the studies of this review, which is called Consensus Nomogram Spectrum for Glioblastoma (CNSgbm) and is accessible through https://bioinfo.henu.edu.cn/nom/NomList.jsp.

Next generation sequencing in adult patients with glioblastoma in Switzerland: a multi-centre decision analysis.

BACKGROUND: Glioblastoma is the most common malignant primary brain tumour in adults and driven by various genomic alterations. Next generation sequencing (NGS) provides timely information about the genetic landscape of tumours and might detect targetable mutations. To date, differences exist in the application and NGS assays used as it remains unclear to what extent these variants may affect clinical decision making. In this survey-based study, we investigated the use of NGS in adult patients with glioblastoma in Switzerland. METHODS: All eight primary care centres for Neuro-Oncology in Switzerland participated in this survey. The NGS assays used as well as the criteria for the application of NGS in newly diagnosed glioblastoma were investigated. Decision trees were analysed for consensus and discrepancies using the objective consensus methodology. RESULTS: Seven out of eight centres perform NGS in patients with newly diagnosed glioblastoma using custom made or commercially available assays. The criteria most relevant to decision making were age, suitability of standard treatment and fitness. NGS is most often used in fitter patients under the age of 60 years who are not suitable for standard therapy, while it is rarely performed in patients in poor general health. CONCLUSION: NGS is frequently applied in glioblastomas in adults in Neuro-Oncology centres in Switzerland despite seldom changing the course of treatment to date.

Critical assessment of DNA adenine methylation in eukaryotes using quantitative deconvolution.

The discovery of N6-methyldeoxyadenine (6mA) across eukaryotes led to a search for additional epigenetic mechanisms. However, some studies have highlighted confounding factors that challenge the prevalence of 6mA in eukaryotes. We developed a metagenomic method to quantitatively deconvolve 6mA events from a genomic DNA sample into species of interest, genomic regions, and sources of contamination. Applying this method, we observed high-resolution 6mA deposition in two protozoa. We found that commensal or soil bacteria explained the vast majority of 6mA in insect and plant samples. We found no evidence of high abundance of 6mA in Drosophila, Arabidopsis, or humans. Plasmids used for genetic manipulation, even those from Dam methyltransferase mutant Escherichia coli, could carry abundant 6mA, confounding the evaluation of candidate 6mA methyltransferases and demethylases. On the basis of this work, we advocate for a reassessment of 6mA in eukaryotes.

Functional In Vitro Assessment of VEGFA/NOTCH2 Signaling Pathway and pRB Proteasomal Degradation and the Clinical Relevance of Mucolipin TRPML2 Overexpression in Glioblastoma Patients.

Glioblastoma (GBM) is the most malignant glioma with an extremely poor prognosis. It is characterized by high vascularization and its growth depends on the formation of new blood vessels. We have previously demonstrated that TRPML2 mucolipin channel expression increases with the glioma pathological grade. Herein by ddPCR and Western blot we found that the silencing of TRPML2 inhibits expression of the VEGFA/Notch2 angiogenic pathway. Moreover, the VEGFA/Notch2 expression increased in T98 and U251 cells stimulated with the TRPML2 agonist, ML2-SA1, or by enforced-TRPML2 levels. In addition, changes in TRPML2 expression or ML2-SA1-induced stimulation, affected Notch2 activation and VEGFA release. An increased invasion capability, associated with a reduced VEGF/VEGFR2 expression and increased vimentin and CD44 epithelial-mesenchymal transition markers in siTRPML2, but not in enforced-TRPML2 or ML2-SA1-stimulated glioma cells, was demonstrated. Furthermore, an increased sensitivity to Doxorubicin cytotoxicity was demonstrated in siTRPML2, whereas ML2-SA1-treated GBM cells were more resistant. The role of proteasome in Cathepsin B-dependent and -independent pRB degradation in siTRPML2 compared with siGLO cells was studied. Finally, through Kaplan-Meier analysis, we found that high TRPML2 mRNA expression strongly correlates with short survival in GBM patients, supporting TRPML2 as a negative prognostic factor in GBM patients.

Joint Clustering of Single-Cell Sequencing and Fluorescence In Situ Hybridization Data for Reconstructing Clonal Heterogeneity in Cancers.

Aneuploidy and whole genome duplication (WGD) events are common features of cancers associated with poor outcomes, but the ways they influence trajectories of clonal evolution are poorly understood. Phylogenetic methods for reconstructing clonal evolution from genomic data have proven a powerful tool for understanding how clonal evolution occurs in the process of cancer progression, but extant methods so far have limited the ability to resolve tumor evolution via ploidy changes. This limitation exists in part because single-cell DNA-sequencing (scSeq), which has been crucial to developing detailed profiles of clonal evolution, has difficulty in resolving ploidy changes and WGD. Multiplex interphase fluorescence in situ hybridization (miFISH) provides a more unambiguous signal of single-cell ploidy changes but it is limited to profiling small numbers of single markers. Here, we develop a joint clustering method to combine these two data sources with the goal of better resolving ploidy changes in tumor evolution. We develop a probabilistic framework to maximize the probability of latent variables given the pre-clustered datasets, which we optimize via Markov chain Monte Carlo sampling combined with linear regression. We validate the method by using simulated data derived from a glioblastoma (GBM) case profiled by both scSeq and miFISH. We further apply the method to two GBM cases with scSeq and miFISH data by reconstructing a phylogenetic tree from the joint clustering results, demonstrating their synergistic value in understanding how focal copy number changes and WGD events can collectively contribute to tumor progression.

Refinement of response assessment in neuro-oncology (RANO) using non-enhancing lesion type and contrast enhancement evolution pattern in IDH wild-type glioblastomas.

BACKGROUND: Updated response assessment in neuro-oncology (RANO) does not consider peritumoral non-enhancing lesion (NEL) and baseline (residual) contrast enhancement (CE) volume. The objective of this study is to explore helpful imaging characteristics to refine RANO for assessing early treatment response (pseudoprogression and time-to-progression [TTP]) in patients with IDH wild-type glioblastoma. METHODS: This retrospective study enrolled 86 patients with IDH wild-type glioblastoma who underwent consecutive MRI examinations before and after concurrent chemoradiotherapy (CCRT). NEL was classified as edema- or tumor-dominant type on pre-CCRT MRI. CE evolution was categorized into 4 patterns based on post-operative residual CE (measurable vs. non-measurable) and CE volume change (same criteria with RANO) during CCRT. Multivariable logistic regression, including clinical parameters, NEL type, and CE evolution pattern, was used to analyze pseudoprogression rate. TTP and OS according to NEL type and CE evolution pattern was analyzed by the Kaplan-Meier method. RESULTS: Pseudoprogression rate was significantly lower (chi-square test, P = .047) and TTP was significantly shorter (hazard ratio [HR] = 2.03, P = .005) for tumor-dominant type than edema-dominant type of NEL. NEL type was the only predictive marker of pseudoprogression on multivariate analysis (odds ratio = 0.26, P = .046). Among CE evolution patterns, TTP and OS was shortest in patients with residual CE compared with those exhibiting new CE (HR = 4.33, P < 0.001 and HR = 3.71, P = .009, respectively). In edema-dominant NEL type, both TTP and OS was stratified by CE evolution pattern (log-rank, P = .001), whereas it was not in tumor-dominant NEL. CONCLUSIONS: NEL type improves prediction of pseudoprogression and, together with CE evolution pattern, further stratifies TTP and OS in patients with IDH wild-type glioblastoma and may become a helpful biomarker for refining RANO.

Quantitative assessment of glioblastoma phenotypes in vitro establishes cell migration as a robust readout of Crk and CrkL activity.

The expression levels of CT10 regulator of kinase (Crk) and Crk-like (CrkL) are elevated in many human cancers, including glioblastoma (GBM), and are believed to contribute to poor prognosis. Although Crk and CrkL have been proposed as therapeutic targets in these tumors, the lack of a reliable, quantitative assay to measure Crk and CrkL activity has hindered development of inhibitors. Here, we knocked down Crk, CrkL, or both using siRNAs in a human GBM cell line, U-118MG, to determine the respective, quantitative contributions of Crk and CrkL to cellular phenotypes. The combined use of specific and potent Crk and CrkL siRNAs induced effective knockdown of CrkII, CrkI, and CrkL. Whereas Crk knockdown did not affect cell morphology, proliferation, adhesion, or invasion, CrkL knockdown caused shrinkage of cells and inhibition of cell proliferation, adhesion, and invasion. Crk/CrkL double knockdown resulted in more pronounced morphological alterations and more robust inhibition of proliferation, adhesion, and invasion. Furthermore, Crk/CrkL double knockdown completely blocked cell migration, and this effect was rescued by transient overexpression of CrkL but not of Crk. Quantification of protein levels indicated that CrkL is expressed more abundantly than CrkII and CrkI in U-118MG cells. These results demonstrate both the predominant role of CrkL and the essential overlapping functions of Crk and CrkL in U-118MG cells. Furthermore, our study indicates that migration of U-118MG cells depends entirely on Crk and CrkL. Thus, impedance-based, real-time measurement of tumor cell migration represents a robust assay for monitoring Crk and CrkL activities.

Assessment of MGMT methylation status using high-performance liquid chromatography in newly diagnosed glioblastoma.

BACKGROUND: The utility of O6-methylguanine-DNA methyltransferase (MGMT) gene promoter methylation status as a prognostic marker in patients with glioblastoma (GBM) has been established. However, the number of CpG sites that must be methylated to cause transcriptional silencing remains unclear, and no significant consensus exists on the optimal method of assessing MGMT methylation. We developed a new high-performance liquid chromatography (HPLC) method that enables accurate analysis of DNA methylation levels using long PCR products. In the present study, we analyzed the MGMT methylation status of 28 isocitrate dehydrogenase-wild-type GBMs treated with temozolomide using ion-exchange HPLC and set the optimal cutoff values. RESULTS: We designed three primers for separate regions (regions 1-3) that had 21 to 38 CpGs for PCR and validated the MGMT promoter methylation status using frozen samples. There was a strong correlation between HPLC and bisulfite sequencing results (R = 0.794). The optimal cutoff values for MGMT methylation in HPLC were determined to allow differentiation of patient prognosis by receiver operating characteristic curve analysis. The cutoff values were 34.15% for region 1, 8.84% for region 2, and 36.72% for region 3. Kaplan-Meyer curve analysis estimated that the most differentiated prognosis was enabled in the setting of 8.84% methylation of MGMT in region 2. Progression-free survival and overall survival were significantly longer for patients in this setting of region 2 methylation (p = 0.00365 and p = 0.00258, respectively). CONCLUSIONS: The combination of our HPLC method and the original primer setting provides a new standard method for determination of MGMT methylation status in patients with GBM and is useful for refining MGMT-based drug selection.

Anti-PD-1 Immunotherapy in Preclinical GL261 Glioblastoma: Influence of Therapeutic Parameters and Non-Invasive Response Biomarker Assessment with MRSI-Based Approaches.

Glioblastomas (GBs) are malignant brain tumours with poor prognosis even after aggressive therapy. Programmed cell death-1 (PD-1) immune checkpoint blockade is a promising strategy in many types of cancer, but its therapeutic effects in GB remain low and associated with immune infiltration. Previous work suggests that oscillations of magnetic resonance spectroscopic imaging (MRSI)-based response pattern with chemotherapy could act as a biomarker of efficient immune system attack onto GBs. The presence of such oscillations with other monotherapies such as anti-PD-1 would reinforce its monitoring potential. Here, we confirm that the oscillatory behaviour of the response biomarker is also detected in mice treated with anti PD-1 immunotherapy both in combination with temozolomide and as monotherapy. This indicates that the spectral pattern changes observed during therapy response are shared by different therapeutic strategies, provided the host immune system is elicited and able to productively attack tumour cells. Moreover, the participation of the immune system in response is also supported by the rate of cured animals observed with different therapeutic strategies (in the range of 50-100% depending on the treatment), which also held long-term immune memory against tumour cells re-challenge. Taken together, our findings open the way for a translational use of the MRSI-based biomarker in patient-tailored GB therapy, including immunotherapy, for which reliable non-invasive biomarkers are still missing.

Preconditioning with INC280 and LDK378 drugs sensitizes MGMT-unmethylated glioblastoma to temozolomide: Pre-clinical assessment.

Temozolomide (TMZ) therapy is the standard of care for patients with glioblastoma (GBM). Clinical studies have shown that elevated levels of DNA repair protein O (6)-methylguanine-DNA methyltransferase (MGMT) or deficiency/defect of DNA mismatch repair (MMR) genes is associated with TMZ resistance in some, but not all, GBM tumors. Another reason for GBM treatment failure is signal redundancy due to coactivation of several functionally linked receptor tyrosine kinases (RTKs), including anaplastic lymphoma kinase (ALK) and c-Met (hepatocyte growth factor receptor). As such, these tyrosine kinases serve as potential targets for GBM therapy. Thus, we tested two novel drugs: INC280 (Capmatinib: a highly selective c-Met receptor tyrosine kinase-RTK inhibitor) and LDK378 (Ceritinib: a highly selective anaplastic lymphoma kinase-ALK inhibitor), aiming to overcome TMZ resistance in MGMT-unmethylated GBM cells in in vitro cell culture models. Treatments were examined using MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay, caspase-3 assay and western blot analysis. Results obtained from our experiments demonstrated that preconditioning with INC280 and LDK378 drugs exhibit increased MMR protein expression, specifically MMR protein MLH1 (MutL Homolog 1) and MSH6 (MutS Homolog 6) and sensitized TMZ in MGMT-unmethylated GBM cells via suppression of ALK and c-Met expression. INC280 and LDK378 plus TMZ also induced apoptosis by modulating downstream signaling of PI3K/AKT/STAT3. Taken together, this data indicates that co-inhibition of ALK and c-MET can enhance growth inhibitory effects in MGMT-unmethylated cells and enhance TMZ sensitivity in-vitro, suggesting c-Met inhibitors combined with ALK-targeting provide a therapeutic benefit in MGMT-unmethylated GBM patients.

Assessment of circulating tumor DNA in cerebrospinal fluid by whole exome sequencing to detect genomic alterations of glioblastoma.

BACKGROUND: Cerebrospinal fluid (CSF) has been demonstrated as a better source of circulating tumor DNA (ctDNA) than plasma for brain tumors. However, it is unclear whether whole exome sequencing (WES) is qualified for detection of ctDNA in CSF. The aim of this study was to determine if assessment of ctDNA in CSF by WES is a feasible approach to detect genomic alterations of glioblastoma. METHODS: CSFs of ten glioblastoma patients were collected pre-operatively at the Department of Neurosurgery, Sun Yat-sen University Cancer Center. ctDNA in CSF and genome DNA in the resected tumor were extracted and subjected to WES. The identified glioblastoma-associated mutations from ctDNA in CSF and genome DNA in the resected tumor were compared. RESULTS: Due to the ctDNA in CSF was unqualified for exome sequencing for one patient, nine patients were included into the final analysis. More glioblastoma-associated mutations tended to be detected in CSF compared with the corresponding tumor tissue samples (3.56 ±â€Š0.75 vs. 2.22 ±â€Š0.32, P = 0.097), while the statistical significance was limited by the small sample size. The average mutation frequencies were similar in CSF and tumor tissue samples (74.1% ±â€Š6.0% vs. 73.8% ±â€Š6.0%, P = 0.924). The R132H mutation of isocitrate dehydrogenase 1 and the G34V mutation of H3 histone, family 3A (H3F3A) which had been reported in the pathological diagnoses were also detected from ctDNA in CSF by WES. Patients who received temozolomide chemotherapy previously or those whose tumor involved subventricular zone tended to harbor more mutations in their CSF. CONCLUSION: Assessment of ctDNA in CSF by WES is a feasible approach to detect genomic alterations of glioblastoma, which may provide useful information for the decision of treatment strategy.

Identifying Disparities in Care in Treating Glioblastoma: A Retrospective Cohort Study of Patients Treated at a Safety-net Versus Private Hospital Setting.

BACKGROUND: Patients of lower socioeconomic status (SES) may experience barriers to their oncologic care, but current data conflict over whether SES affects the prognosis of patients with glioblastoma (GB). OBJECTIVE: We sought to determine whether SES disparities impaired delivery of neuro-oncologic care and affected the prognosis of GB patients. METHODS: The records of GB patients treated from 2010 to 2014 at a safety-net hospital (SNH) or private hospital (PH), both served by 1 academic medical institution, were retrospectively reviewed and compared. Overall survival (OS) and progression-free survival (PFS) were estimated using the Kaplan-Meier method. RESULTS: A total of 55 SNH and 39 PH GB patients were analyzed with median 11-month follow-up. SNH patients were predominantly Hispanic, low income, enrolled in Medicaid, were less likely to receive radiation (89% vs. 100%), took longer to start radiation (41 vs. 29 days), and were less likely to complete radiation treatment (80% vs. 95%). Concurrent and adjuvant temozolomide use were also lower (85% vs. 94% and 60% vs. 71%, respectively). OS and PFS were not significantly different (15 vs. 16 months and 8 vs. 11 months, respectively). On multivariate analysis, adjuvant chemotherapy and RT completion predicted for better OS, whereas hospital type, income, and insurance did not. CONCLUSION: Although GB patients at our SNH received less adjuvant treatment compared with PH, outcomes were similar. Access to multidisciplinary care staffed by academic physicians may play an important role in overcoming socioeconomic barriers to treatment availability and quality at SNHs.

Temozolomide for patients with wild-type isocitrate dehydrogenase (IDH) 1 glioblastoma using propensity score matching.

OBJECTIVE: The isocitrate dehydrogenase (IDH) 1 wild-type glioblastoma (GBM) is a major population of GBM that should be of concern in terms of the efficacy of using Temozolomide (TMZ) in adjuvant treatment. This study aimed to compare the effectiveness of TMZ with radiotherapy (RT) and RT alone in patients with IDH1wild-type GBM using a propensity score matching (PSM) approach. PATIENTS AND METHODS: Newly-diagnosed GBM patients were retrospectively analyzed. The clinical variables were collected from a hospital database. Multivariable analysis and propensity score matching (PSM) were used for adjusting the differences in characteristics among patients. The effect of TMZ on the survival of patients with GBM was evaluated by time-to-event analysis based on the multivariable model and PSM. RESULTS: One hundred and sixty-two patients were included in the unmatched analysis. Overall median survival time was 11 months (95 % CI 9.3-12.6). In the multivariable model, TMZ and RT were associated with significantly longer survival compared with RT alone (Hazard ratio [HR] 0.64, 95 %CI 0.43-0.93). After PSM, each of the 55 patients was assigned to TMZ with RT and RT alone groups. The overall median survival time of matched data was 12.0 months (95 %CI = 10.0-13.9). Additionally, the HR of TMZ with RT was 0.67 (95 %CI 0.46-0.99) in the PSM method. CONCLUSIONS: The present study revealed that the effect of TMZ with RT in IDH1 wild-type GBM patients had advantages in terms of survival by using multivariable analysis and PS approaches. In real-world settings, confounders should be explored and controlled prior to statistical analysis. Also, an economic evaluation of the specific subgroups should be conducted in the future.

Quantitative assessment and clinical relevance of VEGFRs-positive tumor cells in refractory brain tumors.

Vascular endothelial growth factor (VEGF)/VEGF receptor (VEGFR)1 and 2 signaling is a potent activator of tumor angiogenesis. Although the expressions of VEGFR1 and VEGFR2 were initially thought to be limited to the endothelial cells, it is now known that both the receptors are expressed in tumor cells. This is the first study wherein VEGFRs-positive tumor cells are quantitatively evaluated for brain tumors with upregulated VEGF/VEGFR signaling. The percentage of VEGFRs-positive tumor cells was quantitatively evaluated in various brain tumors (10 glioblastomas, 22 neurofibromatosis type 2 [NF2]-related schwannomas, 21 sporadic schwannomas, 27 chordomas, 36 meningiomas, 29 hemangioblastomas, 11 hemangiopericytoma, and 13 ependymomas) using immunohistochemistry. VEGF-A expression was also analyzed using quantitative real-time polymerase chain reaction. Double immunofluorescence staining using anti-PDGFR-ß and anti-CD34 antibody, microvessel density, and vessel diameter were analyzed to evaluate the vascular characteristics. Chordomas demonstrated an extremely higher percentage of VEGFR1 and VEGFR2-positive tumor cells than other tumors. In contrast, meningiomas and hemangiopericytomas showed few VEGFRs-positive tumor cells. The percentage of positive tumor cells in chordomas, hemangioblastomas, and NF2 schwannomas was associated with clinical courses, such as shorter progression free survival, and growth speed. Glioblastomas and NF2 schwannomas showed larger tumor vessels without pericyte coverage. The present study is the first to quantitatively analyze VEGFR1- and VEGFR2- positive tumor cells in various types of refractory brain tumors. This novel parameter significantly correlated with the progressive clinical courses.

Longitudinal assessment of tumor development using cancer avatars derived from genetically engineered pluripotent stem cells.

Many cellular models aimed at elucidating cancer biology do not recapitulate pathobiology including tumor heterogeneity, an inherent feature of cancer that underlies treatment resistance. Here we introduce a cancer modeling paradigm using genetically engineered human pluripotent stem cells (hiPSCs) that captures authentic cancer pathobiology. Orthotopic engraftment of the neural progenitor cells derived from hiPSCs that have been genome-edited to contain tumor-associated genetic driver mutations revealed by The Cancer Genome Atlas project for glioblastoma (GBM) results in formation of high-grade gliomas. Similar to patient-derived GBM, these models harbor inter-tumor heterogeneity resembling different GBM molecular subtypes, intra-tumor heterogeneity, and extrachromosomal DNA amplification. Re-engraftment of these primary tumor neurospheres generates secondary tumors with features characteristic of patient samples and present mutation-dependent patterns of tumor evolution. These cancer avatar models provide a platform for comprehensive longitudinal assessment of human tumor development as governed by molecular subtype mutations and lineage-restricted differentiation.