UCLA

There is a critical need for more effective systemic therapies for the treatment of soft tissue sarcoma and, specifically, undifferentiated sarcoma. Immunotherapy has shown signs of efficacy for the treatment of soft tissue sarcoma, particularly in undifferentiated sarcoma, though selecting the patients who will benefit from immunotherapy remains difficult and unclear. Further studies are needed to characterize the immune landscape of soft tissue sarcoma and to develop strategies to identify patients that are likely to benefit from immunotherapy.

In this study, I investigated the immunologic heterogeneity and identify transcriptomic and genomic correlates of immune cell infiltration in undifferentiated sarcoma. In doing so, I determined the immune cell landscape, the optimal high-throughput tools, and the transcriptomic and genomic changes associated with high and low immune cell infiltration in soft tissue sarcoma.

This study synthesized many datasets and data types for a comprehensive analysis of the immune landscape in soft tissue sarcoma. I first characterized the immune cell landscape in soft tissue sarcoma using flow cytometry data from fresh operative samples (n=105) of multiple soft tissue sarcoma subtypes. I then generated a tissue microarray with matched RNA sequencing data from 60 samples of untreated undifferentiated sarcoma to determine the optimal method of in-silico immune deconvolution, which allows for the expansion of this analysis to other next generation sequencing data. Finally, I synthesized multiple publicly available datasets containing next generation sequencing data (RNA sequencing and whole exome sequencing) from undifferentiated sarcoma samples. This data is combined with data from the aforementioned samples for a total of 193 samples and is used to determine the transcriptomic and genomic correlates of immune cell infiltration in undifferentiated sarcoma.

In the analysis of the flow cytometry data, I found that undifferentiated sarcoma tumors are characterized by a myeloid predominance and a relative abundance of suppressor cells, such as Treg cells and CD11b cells. I additionally found that the immune composition of peripheral blood was associated with intratumoral leukocyte infiltration, and specifically that myeloid-predominant tumor and lymphocyte-predominant blood are mutually exclusive. I then determined the optimal in-silico immune deconvolution tool in undifferentiated sarcoma by determining the correlation between mIF and in-silico immune deconvolution scores. Based on these findings, I suggest the following practices when applying in-silico immune deconvolution tools to undifferentiated sarcoma: (1) Use TIMER to define overall immune cell infiltration. (2) Use MCP counter to define monocyte infiltration or use CIBERSORTx, EPIC, quanTIseq, TIMER, or xCell to define macrophage infiltration. (3) Use caution when using in-silico immune deconvolution tools to define CD8+ T cell infiltration. CIBERSORTx most accurately defines CD8+ T cell immune infiltration, however, there are still many instances when tumors with high CD8+ T cell infiltration will be missed using this technique. (4) Avoid applying in-silico immune deconvolution results to define B cell or CD4+ T cell immune infiltration. Finally, I found that increased copy number changes were associated with low immune cell infiltration in undifferentiated sarcoma. These findings were suggested in both transcriptomic and genomic analyses. Interestingly, this association between CNA and immune invasion were unique to the UPS and DDLPS subtypes of STS, but it was not seen in other subtypes of STS. The mechanisms underlying this association are not clear and warrant further study.

These insights provide necessary information to understand which patients may benefit from immunotherapy and guide future studies to further the treatment of soft tissue sarcoma. These studies provide the groundwork for further investigation in this study of immune cell infiltration in soft tissue sarcoma and provide insights into how we may be able to improve outcomes in this rare and devastating disease. The mechanisms underlying these findings remain unclear and warrant further investigation. A deeper understanding of the drivers of immune cell infiltration, the unique tumor microenvironment in soft tissue sarcoma, and role that chromosomal instability plays in soft tissue sarcoma will hopefully ultimately lead to insights to new, and much-needed, treatments for this disease.