Prognostic prediction of glioblastoma by quantitative assessment of the methylation status of the entire MGMT promoter region.

BACKGROUND: O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation is reported to be a prognostic and predictive factor of alkylating chemotherapy for glioblastoma patients. Methylation specific PCR (MSP) has been most commonly used when the methylation status of MGMT is assessed. However, technical obstacles have hampered the implementation of MSP-based diagnostic tests. We quantitatively analyzed the methylation status of the entire MGMT promoter region and applied this information for prognostic prediction using sequencing technology. METHODS: Between 1998 and 2012, the genomic DNA of 85 tumor samples from newly diagnosed glioblastoma patients was subjected to bisulfite treatment and subdivided into a training set, consisting of fifty-three samples, and a test set, consisting of thirty-two samples. The training set was analyzed by deep Sanger sequencing with a sequencing coverage of up to 96 clones per sample. This analysis quantitatively revealed the degree of methylation of each cytidine phosphate guanosine (CpG) site. Based on these data, we constructed a prognostic prediction system for glioblastoma patients using a supervised learning method. We then validated this prediction system by deep sequencing with a next-generation sequencer using a test set of 32 samples. RESULTS: The methylation status of the MGMT promoter was correlated with progression-free survival (PFS) in our patient population in the training set. The degree of correlation differed among the CpG sites. Using the data from the top twenty CpG sites, we constructed a prediction system for overall survival (OS) and PFS. The system successfully classified patients into good and poor prognosis groups in both the training set (OS, p = 0.0381; PFS, p = 0.00122) and the test set (OS, p = 0.0476; PFS, p = 0.0376). Conventional MSP could not predict the prognosis in either of our sets. (training set: OS; p = 0.993 PFS; p = 0.113, test set: OS; p = 0.326 PFS; p = 0.342). CONCLUSIONS: The prognostic ability of our prediction system using sequencing data was better than that of methylation-specific PCR (MSP). Advances in sequencing technologies will make this approach a plausible option for diagnoses based on MGMT promotor methylation.

Characteristics of Pain During MRI-Guided Focused Ultrasound Thalamotomy.

BACKGROUND: Magnetic resonance imaging-guided focused ultrasound (MRgFUS) has become popular as an incisionless mode of neurosurgical treatment. However, head pain during sonication is common and its pathophysiology remains poorly understood. OBJECTIVE: To explore the characteristics of head pain occurring during MRgFUS thalamotomy. METHODS: Our study comprised 59 patients who answered questions about the pain they experienced during unilateral MRgFUS thalamotomy. The location and features of pain were investigated using a questionnaire including the numerical rating scale (NRS) to estimate maximum pain intensity and the Japanese version of the Short Form of McGill Pain Questionnaire 2 to evaluate the quantitative and qualitative dimensions of pain. Several clinical factors were investigated for possible correlation with pain intensity. RESULTS: Forty-eight patients (81%) reported sonication-related head pain, and the degree of pain was severe (NRS score ≥ 7) in 39 patients (66%). The distribution of sonication-related pain was "localized" in 29 (49%) and "diffuse" in 16 (27%); the most frequent location was the "occipital" region. The pain features most frequently reported were those in the "affective" subscale of the Short Form of McGill Pain Questionnaire 2. Patients with diffuse pain had a higher NRS score and lower skull density ratio than did patients with localized pain. The NRS score negatively correlated with tremor improvement at 6 months post-treatment. CONCLUSION: Most patients in our cohort experienced pain during MRgFUS. The distribution and intensity of pain varied according to the skull density ratio, indicating that the pain might have had different origins. Our results may contribute to the improvement of pain management during MRgFUS.

Altered Thalamic Connectivity Due to Focused Ultrasound Thalamotomy in Patients with Essential Tremor.

BACKGROUND: Although stereotactic ablation surgery is known to ameliorate involuntary movement dramatically, little is known regarding alterations in whole-brain networks due to disruption of the deep brain nucleus. To explore changes in the whole-brain network after thalamotomy, we analyzed structural and functional connectivity alterations using resting-state functional magnetic resonance imaging and diffusion tensor imaging in patients with essential tremor who had undergone focused ultrasound (FUS) thalamotomy. METHODS: Seven patients with intractable essential tremors and 7 age-matched healthy controls were enrolled in the study. The tremor score in essential tremor patients was assessed, and resting-state functional magnetic resonance imaging and diffusion tensor imaging were performed before and 3 months after left ventral intermediate nucleus thalamotomy using FUS. RESULTS: There was a significant improvement in the tremor of the right hand after FUS thalamotomy. Seed-based functional connectivity analysis revealed a significant increase in functional connectivity between the left thalamus and the caudal part of the dorsal premotor cortex after FUS thalamotomy. Structural connectivity analysis did not detect statistically significant changes between before and after FUS. There was no correlation between the changes in functional connectivity and tremor score. CONCLUSIONS: Although the number of cases is small, our results show that functional connectivity between the thalamus and the premotor cortex increases after the amelioration of tremors by FUS thalamotomy. The lack of correlation between increased functional connectivity and clinical tremor scores suggests that the observed increase in functional connectivity may be a compensatory change in the secondary sensorimotor changes that occur after thalamotomy.

Focused Ultrasound Thalamotomy for Refractory Essential Tremor: A Japanese Multicenter Single-Arm Study.

BACKGROUND: Several feasibility studies and a randomized, controlled, multicenter trial have demonstrated the safety and efficacy of unilateral transcranial magnetic resonance-guided focused ultrasound (FUS) lesioning of the ventral intermediate thalamic nucleus in treating essential tremor. OBJECTIVE: To evaluate the safety and efficacy of FUS thalamotomy in a Japanese patient cohort through a prospective, multicenter, single-arm confirmatory trial. METHODS: A total of 35 patients with disabling refractory essential tremor underwent unilateral FUS thalamotomy and were followed up for 12 post-treatment months. Safety was measured as the incidence and severity of treatment-related adverse events. Efficacy was measured as the tremor severity and quality of life improvements using the Clinical Rating Scale for Tremor and Questionnaire for Essential Tremor. RESULTS: The mean skull density ratio (SDR) was 0.47. There was a significant decrease in the mean postural tremor score of the treated hand from baseline to 12 mo by 56.4% (95% CI: 46.7%-66.1%; P < .001), which was maintained at last follow-up. Quality of life improved by 46.3% (mean overall Questionnaire for Essential Tremor score of 17.4 [95% CI: 12.1-22.7]) and there were no severe adverse events. The most frequent adverse event was gait disturbance and all events resolved. CONCLUSION: Unilateral FUS thalamotomy allowed significant and sustained tremor relief and improved the quality of life with an outstanding safety profile. The observed safety and efficacy of FUS thalamotomy were comparable to those reported in a previous multicenter study with a low SDR, and inclusion of the low SDR group did not affect effectiveness.

Conversion of a molecular classifier obtained by gene expression profiling into a classifier based on real-time PCR: a prognosis predictor for gliomas.

BACKGROUND: The advent of gene expression profiling was expected to dramatically improve cancer diagnosis. However, despite intensive efforts and several successful examples, the development of profile-based diagnostic systems remains a difficult task. In the present work, we established a method to convert molecular classifiers based on adaptor-tagged competitive PCR (ATAC-PCR) (with a data format that is similar to that of microarrays) into classifiers based on real-time PCR. METHODS: Previously, we constructed a prognosis predictor for glioma using gene expression data obtained by ATAC-PCR, a high-throughput reverse-transcription PCR technique. The analysis of gene expression data obtained by ATAC-PCR is similar to the analysis of data from two-colour microarrays. The prognosis predictor was a linear classifier based on the first principal component (PC1) score, a weighted summation of the expression values of 58 genes. In the present study, we employed the delta-delta Ct method for measurement by real-time PCR. The predictor was converted to a Ct value-based predictor using linear regression. RESULTS: We selected UBL5 as the reference gene from the group of genes with expression patterns that were most similar to the median expression level from the previous profiling study. The number of diagnostic genes was reduced to 27 without affecting the performance of the prognosis predictor. PC1 scores calculated from the data obtained by real-time PCR showed a high linear correlation (r=0.94) with those obtained by ATAC-PCR. The correlation for individual gene expression patterns (r=0.43 to 0.91) was smaller than for PC1 scores, suggesting that errors of measurement were likely cancelled out during the weighted summation of the expression values. The classification of a test set (n=36) by the new predictor was more accurate than histopathological diagnosis (log rank p-values, 0.023 and 0.137, respectively) for predicting prognosis. CONCLUSION: We successfully converted a molecular classifier obtained by ATAC-PCR into a Ct value-based predictor. Our conversion procedure should also be applicable to linear classifiers obtained from microarray data. Because errors in measurement are likely to be cancelled out during the calculation, the conversion of individual gene expression is not an appropriate procedure. The predictor for gliomas is still in the preliminary stages of development and needs analytical clinical validation and clinical utility studies.