Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Interplay of Sphingolipid Metabolism in Predicting Prognosis of GBM Patients: Towards Precision Immunotherapy

5 Dec 2023

Abstract excerpt

Background: In spite of numerous existing bio-surveillance systems for predicting glioma (GBM) prognosis, enhancing the efficacy of immunotherapy remains an ongoing conundrum. The continual scrutiny of the dynamic interplay between the sphingolipid metabolic pathway and tumor immunophenotypes has unveiled potential implications. However, the intricate orchestration of functional and regulatory mechanisms by long...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Chronic Lymphocytic Leukemia Research
Share to Phagocytosis and Immune Regulation
Share to Sphingolipid Metabolism and Signaling

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Identifiers

PMID: 38164288
DOI: 10.7150/jca.89338

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Interplay of Sphingolipid Metabolism in Predicting Prognosis of GBM Patients: Towards Precision ImmunotherapyPMID 38164288Read ↗

Exploration of prognosis and immune infiltration characteristics in Glioblastoma Multiforme based on Lipid Metabolism related GenesSemantic proximity Read ↗

Unveiling the Molecular Mechanisms of Glioblastoma through an Integrated Network-Based ApproachSemantic proximity Read ↗

Prognostic signatures of sphingolipids: Understanding the immune landscape and predictive role in immunotherapy response and outcomes of hepatocellular carcinomaSemantic proximity Read ↗

Ensemble Machine Learning Approaches Predict Survival in Lower-Grade Glioma Based on Glycosphingolipid Gene Expression and Metabolic ModellingSemantic proximity Read ↗

A Propionate Metabolism-Based Gene Signature Reveals Immunogenomic and Transcriptomic Determinants of Prognosis in Glioblastoma Through Multiomics Integration.Semantic proximity Read ↗

A novel sphingolipid metabolism-related long noncoding RNA signature predicts the prognosis, immune landscape and therapeutic response in pancreatic adenocarcinomaSemantic proximity Read ↗

Lipid Metabolism classification of gliomasSemantic proximity Read ↗

Proteogenomic and metabolomic characterization of human glioblastoma.Semantic proximity Read ↗

Decoding the Sphingolipid Landscape of Clear Cell Renal Cell Carcinoma: A Single-Cell-Guided Prognostic Model Built With 101 Machine Learning.Semantic proximity Read ↗

Lactylation-related gene signatures identify glioma molecular subtypes with prognostic, immunological, and therapeutic implicationsSemantic proximity Read ↗

Proteomic Profiling of Gliomas Unveils Immune and Metabolism-Driven Subtypes with Implications for Anti-Nucleotide Metabolism TherapySemantic proximity Read ↗

Identification of a Novel Disulfideptosis-Related LncRNA Signature and Integrative Analyses in Patients with GliomasSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.