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Record W3093221119 · doi:10.3389/fimmu.2020.585616

Glioblastoma Immune Landscape and the Potential of New Immunotherapies

2020· review· en· W3093221119 on OpenAlexaff
Thomas Daubon, Audrey Hémadou, Irati Romero‐Garmendia, Maya Saleh

Bibliographic record

VenueFrontiers in Immunology · 2020
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmune cells in cancer
Canadian institutionsMcGill University
FundersLigue Contre le CancerConseil National de la Recherche ScientifiqueFondation ARC pour la Recherche sur le CancerAgence Nationale de la Recherche
KeywordsOncolytic virusImmune systemChimeric antigen receptorImmunotherapyMicrogliaGlioblastomaImmune checkpointMedicineMyeloid cellsCancerEvasion (ethics)VirotherapyCancer researchImmunologyMass cytometryImmunosurveillanceBiologyInflammationInternal medicineGene

Abstract

fetched live from OpenAlex

Glioblastoma (GBM) are the most common tumors of the central nervous system and among the deadliest cancers in adults. GBM overall survival has not improved over the last decade despite optimization of therapeutic standard-of-care. While immune checkpoint inhibitors (ICI) have revolutionized cancer care, they unfortunately have little therapeutic success in GBM. Here, we elaborate on normal brain and GBM-associated immune landscapes. We describe the role of microglia and tumor-associated macrophages (TAMs) in immune suppression and highlight the impact of energy metabolism in immune evasion. We also describe the challenges and opportunities of immunotherapies in GBM and discuss new avenues based on harnessing the anti-tumor activity of myeloid cells, vaccines, chimeric antigen receptors (CAR)-T and -NK cells, oncolytic viruses, nanocarriers, and combination therapies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.980
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.233
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations107
Published2020
Admission routes1
Has abstractyes

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