Osteosarcoma and soft-tissue sarcomas with an immune infiltrate express PD-L1: relation to clinical outcome and Th1 pathway activation
Bibliographic record
Abstract
Immune checkpoint proteins, such as PD-L1 and PD-1, are important in several cancers; however, their role in osteosarcoma (OSA) and soft tissue sarcoma (STS) remains unclear. Our aims were to determine whether subsets of OSA/STS harbor tumor-infiltrating lymphocytes (TILs) and express PD-L1, and how PD-L1 expression is related to clinical outcome. Tissue sections of 25 cases each of untreated undifferentiated pleomorphic sarcoma (UPS), myxofibrosarcoma (MFS), liposarcoma (LPS) and 24 of leiomyosarcoma (LMS) were subjected to immunohistochemistry (IHC) for immune cells, PD-L1 and PD-1. RT-qPCR was utilized to quantify levels of PD-L1 mRNA from 33 UPS, 57 MFS and 79 OSA primary-untreated specimens. PD-L1 mRNA levels were tested for their correlation with overall survival in patients presenting without metastases. Transcriptome analysis evaluated biological pathway differences between high and low PD-L1 expressers. A subset of UPS and MFS contained TILs and expressed PD-L1 and PD-1; LMS and LPS did not. PD-L1 levels by IHC and RT-qPCR were positively correlated. PD-L1 over-expression was associated with better survival for UPS and OSA, but not MFS. The Th1 pathway was significantly activated in UPS with high levels of PD-L1 and improved survival. Some sarcoma subtypes harbor TILs and express PD-L1. Patients with UPS and OSA with high levels of PD-L1 had better overall survival than those with low expression levels. Important biological pathways distinguish PD-L1 high and low groups. The stratification of patients with OSA/STS with respect to potential immune therapies may be improved through investigation of the expression of immune cells and checkpoint proteins.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".