Neuro-oncology最新文献

{"title":"Predicting recurrence of meningioma using DNA methylation for clinical practice.","authors":"Karenna J Groff, Matija Snuderl","doi":"10.1093/neuonc/noaf003","DOIUrl":"10.1093/neuonc/noaf003","url":null,"abstract":"","PeriodicalId":19377,"journal":{"name":"Neuro-oncology","volume":" ","pages":"1017-1018"},"PeriodicalIF":16.4,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12083220/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142952460","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Designing a time-dependent therapeutic strategy using CDK4/6 inhibitors in an intracranial ATRT model.","authors":"Brice Martin, Sergio W Guadix, Rekha Sathian, Madeline Laramee, Abhinav Pandey, Ishani Ray, Amy Wang, Ramana Davuluri, Craig J Thomas, Nadia Dahmane, Mark Souweidane","doi":"10.1093/neuonc/noae262","DOIUrl":"10.1093/neuonc/noae262","url":null,"abstract":"<p><strong>Background: </strong>Inhibitors targeting cyclin-dependent kinases 4 and 6 (CDK4/6), crucial for cell cycle regulation, have shown promise in early-stage studies for treating central nervous system (CNS) tumors. However, challenges such as limited CNS penetration, optimal treatment duration, and systemic side effects have impeded their clinical translation for pediatric brain tumors (PBTs).</p><p><strong>Methods: </strong>We evaluated the potency of CDK4/6 inhibitors across various PBT cell lines, focusing particularly on palbociclib against atypical teratoid rhabdoid tumor (ATRT) with cell viability assays and gene expression analysis. Additionally, we assessed the efficacy and safety of intrathecal (IT) delivery of palbociclib through neurotoxicity and pharmacokinetic studies, along with survival assessments in murine leptomeningeal ATRT models.</p><p><strong>Results: </strong>Palbociclib showed the highest potency across various PBT cells, with extended treatments reducing growth inhibition 50 (GI50) values from the micromolar to nanomolar range. It suppressed critical cell cycle genes (CCNB1, CCNA2, CDK1) in BT16 ATRT cells. Neurotoxicity (GFAP, CD45, NeuN, Iba1) and pharmacokinetic assays confirmed IT route as a feasible and effective method for delivering palbociclib to the cerebrospinal fluid (CSF), avoiding systemic toxicity and enhancing drug concentration to the brain. Finally, metronomic IT delivery using an osmotic pump (OP, 48 mg/kg) increased survival in 2 murine leptomeningeal ATRT models, showcasing its potential as a novel therapy for leptomeningeal tumors.</p><p><strong>Conclusions: </strong>Metronomic IT delivery of palbociclib enhances drug efficacy and safety, improves survival, and offers a promising treatment strategy for PBTs with CSF dissemination.</p>","PeriodicalId":19377,"journal":{"name":"Neuro-oncology","volume":" ","pages":"1076-1091"},"PeriodicalIF":16.4,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12083234/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142829539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning-based prognostic subgrouping of glioblastoma: A multicenter study.","authors":"Hamed Akbari, Spyridon Bakas, Chiharu Sako, Anahita Fathi Kazerooni, Javier Villanueva-Meyer, Jose A Garcia, Elizabeth Mamourian, Fang Liu, Quy Cao, Russell T Shinohara, Ujjwal Baid, Alexander Getka, Sarthak Pati, Ashish Singh, Evan Calabrese, Susan Chang, Jeffrey Rudie, Aristeidis Sotiras, Pamela LaMontagne, Daniel S Marcus, Mikhail Milchenko, Arash Nazeri, Carmen Balana, Jaume Capellades, Josep Puig, Chaitra Badve, Jill S Barnholtz-Sloan, Andrew E Sloan, Vachan Vadmal, Kristin Waite, Murat Ak, Rivka R Colen, Yae Won Park, Sung Soo Ahn, Jong Hee Chang, Yoon Seong Choi, Seung-Koo Lee, Gregory S Alexander, Ayesha S Ali, Adam P Dicker, Adam E Flanders, Spencer Liem, Joseph Lombardo, Wenyin Shi, Gaurav Shukla, Brent Griffith, Laila M Poisson, Lisa R Rogers, Aikaterini Kotrotsou, Thomas C Booth, Rajan Jain, Matthew Lee, Abhishek Mahajan, Arnab Chakravarti, Joshua D Palmer, Dominic DiCostanzo, Hassan Fathallah-Shaykh, Santiago Cepeda, Orazio Santo Santonocito, Anna Luisa Di Stefano, Benedikt Wiestler, Elias R Melhem, Graeme F Woodworth, Pallavi Tiwari, Pablo Valdes, Yuji Matsumoto, Yoshihiro Otani, Ryoji Imoto, Mariam Aboian, Shinichiro Koizumi, Kazuhiko Kurozumi, Toru Kawakatsu, Kimberley Alexander, Laveniya Satgunaseelan, Aaron M Rulseh, Stephen J Bagley, Michel Bilello, Zev A Binder, Steven Brem, Arati S Desai, Robert A Lustig, Eileen Maloney, Timothy Prior, Nduka Amankulor, MacLean P Nasrallah, Donald M O'Rourke, Suyash Mohan, Christos Davatzikos","doi":"10.1093/neuonc/noae260","DOIUrl":"10.1093/neuonc/noae260","url":null,"abstract":"<p><strong>Background: </strong>Glioblastoma (GBM) is the most aggressive adult primary brain cancer, characterized by significant heterogeneity, posing challenges for patient management, treatment planning, and clinical trial stratification.</p><p><strong>Methods: </strong>We developed a highly reproducible, personalized prognostication, and clinical subgrouping system using machine learning (ML) on routine clinical data, magnetic resonance imaging (MRI), and molecular measures from 2838 demographically diverse patients across 22 institutions and 3 continents. Patients were stratified into favorable, intermediate, and poor prognostic subgroups (I, II, and III) using Kaplan-Meier analysis (Cox proportional model and hazard ratios [HR]).</p><p><strong>Results: </strong>The ML model stratified patients into distinct prognostic subgroups with HRs between subgroups I-II and I-III of 1.62 (95% CI: 1.43-1.84, P < .001) and 3.48 (95% CI: 2.94-4.11, P < .001), respectively. Analysis of imaging features revealed several tumor properties contributing unique prognostic value, supporting the feasibility of a generalizable prognostic classification system in a diverse cohort.</p><p><strong>Conclusions: </strong>Our ML model demonstrates extensive reproducibility and online accessibility, utilizing routine imaging data rather than complex imaging protocols. This platform offers a unique approach to personalized patient management and clinical trial stratification in GBM.</p>","PeriodicalId":19377,"journal":{"name":"Neuro-oncology","volume":" ","pages":"1102-1115"},"PeriodicalIF":16.4,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12083074/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142813844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Validation and next-generation update of a DNA methylation-based recurrence predictor for meningioma: A multicenter prospective study.","authors":"Alexander P Landry, Justin Z Wang, Vikas Patil, Chloe Gui, Yasin Mamatjan, Zeel Patel, Rebecca Yakubov, Ramneet Kaloti, Parnian Habibi, Mark Wilson, Andrew Ajisebutu, Yosef Ellenbogen, Qingxia Wei, Olivia Singh, Julio Sosa, Sheila Mansouri, Christopher Wilson, Aaron A Cohen-Gadol, Piiamaria Virtanen, Noah Burket, Matthew Blackwell, Jenna Koenig, Anthony Alfonso, Joseph Davis, Mohamed A Zaazoue, Ghazaleh Tabatabai, Marcos Tatagiba, Felix Behling, Jill S Barnholtz-Sloan, Andrew E Sloan, Silky Chotai, Lola B Chambless, Alireza Mansouri, Felix Ehret, David Capper, Derek S Tsang, Kenneth Aldape, Andrew Gao, Farshad Nassiri, Gelareh Zadeh","doi":"10.1093/neuonc/noae236","DOIUrl":"10.1093/neuonc/noae236","url":null,"abstract":"<p><strong>Background: </strong>We previously developed a DNA methylation-based risk predictor for meningioma, which has been used locally in a prospective fashion since its original publication. As a follow-up, we validate this model using a large prospective cohort and introduce a streamlined next-generation predictor compatible with newer methylation arrays.</p><p><strong>Methods: </strong>Genome-wide methylation profiles were generated with the Illumina EPICArray. The performance of our next-generation predictor was compared with our original model and standard-of-care 2021 WHO grade using time-dependent receiver operating characteristic curves. An nomogram was generated by incorporating our methylation predictor with WHO grade and the extent of resection.</p><p><strong>Results: </strong>A total of 1347 meningioma cases were utilized in the study, including 469 prospective cases from 3 institutions and an external cohort of 100 WHO grade 2 cases for model validation. Both the original and next-generation models significantly outperform the 2021 WHO grade in predicting early postoperative recurrence. Dichotomizing patients into grade-specific risk subgroups was predictive of outcomes within both WHO grades 1 and 2 tumors (P < .05), whereas all WHO grade 3 tumors were considered high-risk. Multivariable Cox regression demonstrated the benefit of adjuvant radiotherapy (RT) in high-risk cases specifically, reinforcing its informative role in clinical decision-making. Finally, our next-generation predictor contains nearly 10-fold fewer features than the original model, allowing for targeted arrays.</p><p><strong>Conclusions: </strong>This next-generation DNA methylation-based meningioma outcome predictor significantly outperforms the 2021 WHO grading in predicting time to recurrence. We make this available as a point-and-click tool that will improve prognostication, inform patient selection for RT, and allow for molecularly stratified clinical trials.</p>","PeriodicalId":19377,"journal":{"name":"Neuro-oncology","volume":" ","pages":"1004-1016"},"PeriodicalIF":16.4,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12083223/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142583595","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Meningiomas: Sex-specific differences and prognostic implications of a chromosome X loss.","authors":"Natalie Berghaus, Thomas Hielscher, Dilan Savran, Daniel Schrimpf, Sybren L N Maas, Matthias Preusser, Michael Weller, Till Acker, Christel Herold-Mende, Wolfgang Wick, Andreas von Deimling, Felix Sahm","doi":"10.1093/neuonc/noae239","DOIUrl":"10.1093/neuonc/noae239","url":null,"abstract":"<p><strong>Background: </strong>Meningiomas are the most common primary intracranial tumors in adults. Several studies proposed new stratification systems with a more accurate risk prediction than the WHO grading, eg, based on methylation and copy-number variations (CNVs). Yet, common shortcomings in these analyses are either a lack of stratification by sex of patients or excluding the gonosomes from CNV assessment.</p><p><strong>Methods: </strong>Within this study, DNA methylation array data from 7424 meningioma samples as well as targeted sequencing, clinical annotations, and morphology subtyping of 796 samples were examined for differences between females and males regarding mutations, methylation classes, CNVs, and histology.</p><p><strong>Results: </strong>Meningiomas from females accounted for about 53% of the malignant tumors and present a loss of one X chromosome in 57% of these malignant cases. In the group of benign tumors, females comprised about 75% of the patients. Therein, a loss of one X chromosome was detected in only about 10% of the cases but was associated with a significantly worse progression-free survival.</p><p><strong>Conclusions: </strong>Although genomic instability is a common feature of malignant meningiomas, particularly loss of the X chromosome in tumors of female patients in otherwise histologically and molecularly low-risk tumors confers higher risk. Hence, the gonosomal copy-number status can be leveraged for increased diagnostic accuracy.</p>","PeriodicalId":19377,"journal":{"name":"Neuro-oncology","volume":" ","pages":"1019-1028"},"PeriodicalIF":16.4,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12083225/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142625036","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The time has come for an integrated and multiscale grading system for oligodendrogliomas IDH-mutant and 1p/19q co-deleted mixing imaging and histomolecular parameters.","authors":"Johan Pallud","doi":"10.1093/neuonc/noaf022","DOIUrl":"10.1093/neuonc/noaf022","url":null,"abstract":"","PeriodicalId":19377,"journal":{"name":"Neuro-oncology","volume":" ","pages":"1128-1129"},"PeriodicalIF":16.4,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12083221/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144013296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reply to \"The time has come for an integrated and multiscale grading system for oligodendrogliomas IDH-mutant and 1p/19q co-deleted mixing imaging and histomolecular parameters\".","authors":"Dominique Figarella-Branger, Caroline Dehais, Carole Colin, François Ducray","doi":"10.1093/neuonc/noaf023","DOIUrl":"10.1093/neuonc/noaf023","url":null,"abstract":"","PeriodicalId":19377,"journal":{"name":"Neuro-oncology","volume":" ","pages":"1130-1131"},"PeriodicalIF":16.4,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12083217/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144009786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Canonical amplifications and CDKN2A/B loss refine IDH1/2-mutant astrocytoma prognosis.","authors":"Hia S Ghosh, Ruchit V Patel, Elizabeth B Claus, Luis Nicolas Gonzalez Castro, Patrick Y Wen, Keith L Ligon, David M Meredith, Wenya Linda Bi","doi":"10.1093/neuonc/noae258","DOIUrl":"10.1093/neuonc/noae258","url":null,"abstract":"<p><strong>Background: </strong>Molecular features have been incorporated alongside histologic criteria to improve glioma diagnostics and prognostication. CDKN2A/B homozygous-loss associates with worse survival in IDH1/2-mutant astrocytomas (IDHmut-astrocytomas), the presence of which denotes a grade 4 tumor independent of histologic features. However, no molecular features distinguish survival amongst histologically defined grade 2 and 3 IDHmut-astrocytomas.</p><p><strong>Methods: </strong>We assembled a cohort of patients ≥19 years old diagnosed with an IDHmut-astrocytoma between 1989 and 2020 from public datasets and several academic medical centers. Multivariate modeling and unbiased clustering were used to stratify risk.</p><p><strong>Results: </strong>We identified 998 IDHmut-astrocytoma patients (41.5% female; 85.6% white). Tumor grade, CDKN2A/B loss, and/or ≥1 focal amplification were associated with reduced survival. Grade 2/3 patients with intact CDKN2A/B and no focal amplifications survived the longest (OS 205.7 months). Survival for grade 2/3 cases with either CDKN2A/B hemizygous-loss or focal amplifications (80.4, 88.7 months respectively) did not differ significantly from grade 4 cases with intact CDKN2A/B and no amplifications (91.5 months, P = .93). Grade 4 patients with either hemizygous or homozygous loss of CDKN2A/B had the shortest survival (OS 31.9, 32.5 months respectively), followed by grade 4 cases with intact CDKN2A/B and focal gene amplifications (OS 55.9 months). Integrating CDKN2A/B status and amplifications alongside histopathologic grade refined overall survival prediction. Unbiased clustering revealed 9 distinct molecular profiles, with differential survival. IDHmut-astrocytomas with any CDKN2A/B loss clustered together, regardless of grade, and exhibited the poorest outcomes.</p><p><strong>Conclusions: </strong>Combining CDKN2A/B hemizygous-loss and focal gene amplifications reveals a group of IDHmut-astrocytoma patients with an intermediate prognosis, refining IDHmut-astrocytoma classification.</p>","PeriodicalId":19377,"journal":{"name":"Neuro-oncology","volume":" ","pages":"993-1003"},"PeriodicalIF":16.4,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12083226/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142709522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pre-radiation targeted therapy for highly selected patients with newly diagnosed glioblastoma: New tricks for an old dog?","authors":"Macarena I de la Fuente, Andrew B Lassman","doi":"10.1093/neuonc/noaf014","DOIUrl":"10.1093/neuonc/noaf014","url":null,"abstract":"","PeriodicalId":19377,"journal":{"name":"Neuro-oncology","volume":" ","pages":"897-899"},"PeriodicalIF":16.4,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12083216/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143033750","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development and validation of a clinical risk model for postoperative outcome in newly diagnosed glioblastoma: A report of the RANO resect group.","authors":"Philipp Karschnia, Jacob S Young, Gilbert C Youssef, Antonio Dono, Levin Häni, Tommaso Sciortino, Francesco Bruno, Stephanie T Juenger, Nico Teske, Jorg Dietrich, Michael Weller, Michael A Vogelbaum, Martin van den Bent, Juergen Beck, Niklas Thon, Jasper K W Gerritsen, Shawn Hervey-Jumper, Daniel P Cahill, Susan M Chang, Roberta Rudà, Lorenzo Bello, Oliver Schnell, Yoshua Esquenazi, Maximilian I Ruge, Stefan J Grau, Raymond Y Huang, Patrick Y Wen, Mitchel S Berger, Annette M Molinaro, Joerg-Christian Tonn","doi":"10.1093/neuonc/noae231","DOIUrl":"10.1093/neuonc/noae231","url":null,"abstract":"<p><strong>Background: </strong>Following surgery, patients with newly diagnosed glioblastoma frequently enter clinical trials. Nuanced risk assessment is warranted to reduce imbalances between study arms. Here, we aimed (I) to analyze the interactive effects of residual tumor with clinical and molecular factors on outcome and (II) to define a postoperative risk assessment tool.</p><p><strong>Methods: </strong>The response assessment in neuro-oncology (RANO) resect group retrospectively compiled an international, seven-center training cohort of patients with newly diagnosed glioblastoma. The combined associations of residual tumor with molecular or clinical factors and survival were analyzed, and recursive partitioning analysis was performed for risk modeling. The resulting model was prognostically verified in a separate external validation cohort.</p><p><strong>Results: </strong>Our training cohort compromised 1003 patients with newly diagnosed isocitrate dehydrogenase-wildtype glioblastoma. Residual tumor, O6-methylguanine DNA methyltransferase (MGMT) promotor methylation status, age, and postoperative Karnofsky Performance Score were prognostic for survival and incorporated into regression tree analysis. By individually weighting the prognostic factors, an additive score (range, 0-9 points) integrating these four variables distinguished patients with low (0-2 points), intermediate (3-5 points), and high risk (6-9 points) for inferior survival. The prognostic value of our risk model was retained in treatment-based subgroups and confirmed in an external validation cohort of 258 patients with glioblastoma. Compared to previously postulated models, goodness-of-fit measurements were superior for our model.</p><p><strong>Conclusions: </strong>The novel RANO risk model serves as an easy-to-use, yet highly prognostic tool for postoperative patient stratification prior to further therapy. The model may serve to guide patient management and reduce imbalances between study arms in prospective trials.</p>","PeriodicalId":19377,"journal":{"name":"Neuro-oncology","volume":" ","pages":"1046-1060"},"PeriodicalIF":16.4,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12083231/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142569113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}