Characterization of the tumour microenvironment phenotypes in malignant tissues and pleural effusion from advanced osteoblastic osteosarcoma patients.

PURPOSE

Malignant pleural effusion (MPE) is an adverse prognostic factor in patients with osteoblastic osteosarcoma; however, the cellular contexts of MPE are largely unknown.

EXPERIMENTAL DESIGN

We performed single-cell RNA-sequencing (scRNA-seq) on 27 260 cells from seven MPE samples and 91 186 cells from eight osteosarcoma tissues, including one recurrent, one lung metastasis and six primary tumour (PT) samples, to characterize their tumour microenvironment.

RESULTS

Thirteen main cell groups were identified in osteosarcoma tumour and MPE samples. Immune cells dominate the cellular contexts in MPE with more T/NK cells and less osteoclasts compared to PT samples. Of T/NK cells, CD8 GNLY , CD8 KLRC2 T cells and FCGR3A NK cells were enriched in MPE but CD4 FOXP3 Tregs were enriched in PT samples. Naïve IGHD B and immune regulatory IGHA1 B cells were largely identified in MPE, whereas bone metabolism-related CLEC11A B cells were significantly enriched in osteosarcoma PT. M2-type TAMs, including CLEC11A_TAM, C1QC_TAM and Prolif_TAMs, among myeloid cells were enriched in PT, which may suppress cytotoxicity activities of T cells through multiple ligand-receptor interactions. Mature LAMP3 DCs were transformed from CD1C DC and CLEC9A DC sub-clusters when exposure to tumour alloantigens, which may improve T cell cytotoxicity activities on tumour cells under anti-PD-L1 treatments. In further, immune cells from MPE usually present up-regulated glycolysis and down-regulated oxidative phosphorylation and riboflavin metabolism activities compared to those in PT samples.

CONCLUSIONS

Our study provided a novel cellular atlas of MPE and PT in patients with advanced osteosarcoma, which may provide potential therapeutic targets in the future.

© 2022 The Authors. Clinical and Translational Medicine published by John Wiley & Sons Australia, Ltd on behalf of Shanghai Institute of Clinical Bioinformatics.