RESUMO
The assessment of chemotherapy response in osteosarcoma (OS) based on the average percentage of viable cells is limited, as it overlooks the spatial heterogeneity of tumor cell response (foci of resistant cells), immune microenvironment, and bone microarchitecture. Despite the resulting positive classification for response to chemotherapy, some patients experience early metastatic recurrence, demonstrating that our conventional tools for evaluating treatment response are insufficient. We studied the interactions between tumor cells, immune cells (lymphocytes, histiocytes, and osteoclasts), and bone extracellular matrix (ECM) in 18 surgical resection samples of OS using multiplex and conventional immunohistochemistry (IHC: CD8, CD163, CD68, and SATB2), combined with multiscale characterization approaches in territories of good and poor response (GRT/PRT) to treatment. GRT and PRT were defined as subregions with <10% and ≥10% of viable tumor cells, respectively. Local correlations between bone ECM porosity and density of immune cells were assessed in these territories. Immune cell density was then correlated to overall patient survival. Two patterns were identified for histiocytes and osteoclasts. In poor responder patients, CD68 osteoclast density exceeded that of CD163 histiocytes but was not related to bone ECM load. Conversely, in good responder patients, CD163 histiocytes were more numerous than CD68 osteoclasts. For both of them, a significant negative local correlation with bone ECM porosity was found (P < .01). Moreover, in PRT, multinucleated osteoclasts were rounded and intermingled with tumor cells, whereas in GRT, they were elongated and found in close contact with bone trabeculae. CD8 levels were always low in metastatic patients, and those initially considered good responders rapidly died from their disease. The specific recruitment of histiocytes and osteoclasts within the bone ECM, and the level of CD8 represent new features of OS response to treatment. The associated prognostic signatures should be integrated into the therapeutic stratification algorithm of patients after surgery.