Abstract 4134: Immune infiltration and PD-L1 expression in the tumor microenvironment are prognostic in osteosarcoma
Bibliographic record
Abstract
Abstract Purpose: Over the past four decades, osteosarcoma (OS) survival rates have remained stagnant. There is a need to identify novel therapies to target OS. In this study we examined the expression of Programed Death Ligand 1 (PD-L1) and defined the tumor microenvironment in OS in order to assess the feasibility of utilizing immune checkpoint inhibitors as a treatment modality. Experimental Design: PD-L1 expression in OS was examined in two patient cohorts using immunohistochemistry (IHC) (n = 48, n = 59) and expression was validated using quantitative real time PCR (qRT-PCR) (n = 21) and western blotting (n = 9). IHC was used to determine presence of tumor infiltrating lymphocytes and antigen presenting cells (APCs) in the tumor. Expression of PD-L1 was correlated with the presence of immune cells and with event free survival in OS. Results: PD-L1 is expressed in up to 25% of primary OS tumors. Of the PD-L1 positive tumors the majority were also PD-1 positive (92% vs 8%, p = 0.002). In addition, the presence of immune cells in the tumor mass was significantly associated with PD-L1 expression. Although all immune cell types examined were present in OS, only infiltration by APCs, specifically CD1a positive dendritic cells (48.6% vs. 51.4%, p = 0.0010) and CD68 positive macrophages (70.3% vs. 29.7%, p = 0.0316), was associated with worse outcomes. PD-L1 expression was significantly associated with worsened survival (21.6% pos. vs. 78.4% neg., p = 0.0146). Conclusions: For the first time we have identified PD-L1 expression or presence of CD1a or CD68 positive antigen presenting cells as prognostic markers for worsened outcome in OS. Furthermore, we show that IHC is a valid detection method for PD-L1 in OS. With up to 25% of OS patients expressing PD-L1, this study provides rational for targeting the PD-L1:PD-1 axis for immunotherapy in OS. Citation Format: Pratistha Koirala, Michael Roth, Jonathan Gill, Jordan Chinai, Sajida Piperdi, David Geller, Bang Hoang, Vincent Poon, Xingxing Zang, Richard Gorlick. Immune infiltration and PD-L1 expression in the tumor microenvironment are prognostic in osteosarcoma. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4134.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".