High tumour mutation burden improves overall survival in solid tumours treated with immune checkpoint inhibitors
High Mutation Counts May Predict Better Cancer Survival Outcomes
This systematic review and meta-analysis evaluated 5278 patients with solid tumours treated with immune checkpoint inhibitors or chemotherap…
High mutation counts in tumors may help predict who will survive longer when taking powerful immune-boosting cancer drugs
Observational study identifies four immune subtypes in newly-diagnosed glioma grades 2-4 among 354 patients
New immune map shows how glioma types affect survival chances
This primary research article describes an observational study of 354 patients with newly-diagnosed glioma grades 2-4. The authors used mult…
A new map of immune cells in brain tumors reveals four types that predict survival and guide future treatment choices for patients.
Narrative review suggests multi-omics AI models improve glioma radiotherapy response prediction over single-modality approaches.
Glioma Radiotherapy Gets Smarter With Biomarker-Guided Dosing
This narrative review synthesizes evidence regarding multi-omics artificial intelligence models for predicting radiotherapy response in glio…
New biomarkers may help doctors tailor radiation doses for glioma patients, improving outcomes and reducing side effects.
Systematic review and meta-analysis of intra-arterial cerebral infusion for glioma patients
Direct Drug Delivery May Help Brain Tumors
This systematic review and meta-analysis evaluated the safety and efficacy of selective intra-arterial cerebral infusion with blood-brain ba…
Imagine having a powerful medicine that stays right where it needs to work, instead of traveling through your whole body.
Unsupervised clustering of glioma RNAseq data shows diagnostic and prognostic potential
AI-powered analysis reveals hidden brain tumor subtypes with survival links
This unsupervised clustering analysis of public TCGA glioma RNAseq data (n=692) found high diagnostic concordance and prognostic separation.…
A new AI method sorted brain tumors into groups that matched clinical diagnoses 91% of the time and uncovered subtypes tied to survival.
Radiomics from edema zone predicts progression-free survival in postoperative glioma patients
New MRI Scan Predicts Brain Tumor Return With High Accuracy
A retrospective cohort study of 89 postoperative glioma patients found that a radiomics model from the 2-cm edema zone on MRI predicted 1-ye…
A new MRI scan reads brain swelling patterns to predict if a brain tumor will grow back before symptoms appear.
Retrospective cohort of 443 glioma patients analyzed under successive WHO classifications from 2007 to 2021.
Study reviews glioma diagnosis changes with updated WHO classification criteria
This retrospective analysis of a cohort from a high-volume Latin American center evaluated 443 patients undergoing elective tumor surgery be…
New WHO rules mean nearly a quarter of brain tumors in Latin America are now labeled 'not otherwise specified' due to limited molecular test…
Narrative review examines multimodal AI for glioma using neuroimaging and hematologic biomarkers.
AI May Help Doctors Spot Brain Tumors Without Surgery
This narrative review explores the potential of multimodal artificial intelligence (AI) integrating neuroimaging and hematologic biomarkers …
This approach could make brain tumor diagnosis and monitoring less invasive and more precise.
Multi-omics integration identifies candidate genes and cell-type-specific effects in glioma.
Could genetic clues finally pinpoint the right cells to target in deadly brain tumors?
This computational analysis integrated GWAS, bulk tissue, and single-cell multi-omics data to investigate glioma. The study prioritized 11 h…
A new analysis of genetic maps shows deadly brain tumors drive growth by increasing communication between support cells and nerve cells.
Radiomics models predict IDH mutation status and survival in glioma patients across discovery and validation cohorts.
Can scans predict glioma risks without surgery? New models show promise but need more proof.
This multicenter cohort study evaluated radiomics-based machine learning models in 638 glioma patients to predict isocitrate dehydrogenase (…
Computer scans can spot dangerous brain tumor patterns without surgery, but accuracy drops when tested on new patients, so doctors still nee…
Deep learning QTMnet shows potential for glioma grading versus traditional 2CXM model
AI method shows promise for classifying brain tumor severity in small study
A study of 30 glioma patients compared a deep neural network-based perfusion estimation method (QTMnet) to a traditional two-compartment exc…
New AI analysis of brain scans outperformed traditional methods at telling the difference between low and high severity tumors in a small te…
Bibliometric analysis identifies 100 most-cited articles on proton therapy for glioma
Where is the research on proton therapy for brain tumors heading?
A bibliometric analysis of 100 highly-cited articles on proton therapy for glioma found the United States leads in publications, with Massac…
A new analysis of the top 100 studies on proton therapy for brain tumors shows the United States leads the field, with Massachusetts General…