Distinct immune escape and microenvironment between RG-like and pri-OPC-like glioma revealed by single-cell RNA-seq analysis
Bibliographic record
Abstract
The association of neurogenesis and gliogenesis with glioma remains unclear. By conducting single-cell RNA-seq analyses on 26 gliomas, we reported their classification into primitive oligodendrocyte precursor cell (pri-OPC)-like and radial glia (RG)-like tumors and validated it in a public cohort and TCGA glioma. The RG-like tumors exhibited wild-type isocitrate dehydrogenase and tended to carry EGFR mutations, and the pri-OPC-like ones were prone to carrying TP53 mutations. Tumor subclones only in pri-OPC-like tumors showed substantially down-regulated MHC-I genes, suggesting their distinct immune evasion programs. Furthermore, the two subgroups appeared to extensively modulate glioma-infiltrating lymphocytes in distinct manners. Some specific genes not expressed in normal immune cells were found in glioma-infiltrating lymphocytes. For example, glial/glioma stem cell markers OLIG1/PTPRZ1 and B cell-specific receptors IGLC2/IGKC were expressed in pri-OPC-like and RG-like glioma-infiltrating lymphocytes, respectively. Their expression was positively correlated with those of immune checkpoint genes (e.g., LGALS33) and poor survivals as validated by the increased expression of LGALS3 upon IGKC overexpression in Jurkat cells. This finding indicated a potential inhibitory role in tumor-infiltrating lymphocytes and could provide a new way of cancer immune evasion.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".