Glioblastoma Stem Cells as Targets for Emerging Precision Immunotherapies and Molecular Treatments

Advances in organoid and other three-dimensional culture systems, single-cell and spatial transcriptomics, multi-omics, and high-resolution imaging are reshaping our understanding of the cellular origins and evolutionary trajectories of glioblastoma. When integrated with modern data science approaches, these technologies enable the construction of increasingly detailed molecular biographies of normal neural stem and progenitor cells as well as malignant stem-like cellular states. Such molecular biographies illuminate how developmental programs, cellular plasticity, and microenvironmental cues are co-opted during gliomagenesis. At the same time, progress in machine learning, immunotherapy, and precision molecular targeting is beginning to translate these biological insights into therapeutic strategies that specifically disrupt glioblastoma stem-like states. Together, these converging approaches provide a conceptual and technological framework for improved tumor modeling, earlier detection, and increasingly personalized therapies for malignant gliomas.

Authors

Institutions

Publication Details

Journal
Cells
Published
2026-04-26
DOI
https://doi.org/10.3390/cells15090783
Primary Topic
Glioma Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Glioblastoma Stem Cells as Targets for Emerging Precision Immunotherapies and Molecular Treatments

Dennis A. Steindler, Katherine Karakoula
Cells
Glioma Diagnosis and Treatment
article

Glioblastoma Stem Cells as Targets for Emerging Precision Immunotherapies and Molecular Treatments

Dennis A. Steindler, Katherine Karakoula
article en

Abstract

Advances in organoid and other three-dimensional culture systems, single-cell and spatial transcriptomics, multi-omics, and high-resolution imaging are reshaping our understanding of the cellular origins and evolutionary trajectories of glioblastoma. When integrated with modern data science approaches, these technologies enable the construction of increasingly detailed molecular biographies of normal neural stem and progenitor cells as well as malignant stem-like cellular states. Such molecular biographies illuminate how developmental programs, cellular plasticity, and microenvironmental cues are co-opted during gliomagenesis. At the same time, progress in machine learning, immunotherapy, and precision molecular targeting is beginning to translate these biological insights into therapeutic strategies that specifically disrupt glioblastoma stem-like states. Together, these converging approaches provide a conceptual and technological framework for improved tumor modeling, earlier detection, and increasingly personalized therapies for malignant gliomas.

CellsVol. 15(9)
University of North Carolina at Chapel Hill (US), University of Wolverhampton (GB), Research Triangle Park Foundation (US)
Openalex Percentile: Top 7%
Glioma Diagnosis and Treatment
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.