AUTHOR=Lazcano Rossana , Barreto Carmelia M. , Salazar Ruth , Carapeto Fernando , Traweek Raymond S. , Leung Cheuk H. , Gite Swati , Mehta Jay , Ingram Davis R. , Wani Khalida M. , Vu Kim-Anh T. , Parra Edwin R. , Lu Wei , Zhou Jianling , Witt Russell G. , Cope Brandon , Thirasastr Prapassorn , Lin Heather Y. , Scally Christopher P. , Conley Anthony P. , Ratan Ravin , Livingston J. Andrew , Zarzour Alexandra M. , Ludwig Joseph , Araujo Dejka , Ravi Vinod , Patel Shreyaskumar , Benjamin Robert , Wargo Jennifer , Wistuba Ignacio I. , Somaiah Neeta , Roland Christina L. , Keung Emily Z. , Solis Luisa , Wang Wei-Lien , Lazar Alexander J. , Nassif Elise F. TITLE=The immune landscape of undifferentiated pleomorphic sarcoma JOURNAL=Frontiers in Oncology VOLUME=12 YEAR=2022 URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2022.1008484 DOI=10.3389/fonc.2022.1008484 ISSN=2234-943X ABSTRACT=Introduction

Undifferentiated pleomorphic sarcoma (UPS) can be associated with a relatively dense immune infiltration. Immune checkpoint inhibitors (anti-PD1, anti-PDL1, and anti-CTLA4) are effective in 20% of UPS patients. We characterize the immune microenvironment of UPS and its association with oncologic outcomes.

Material and methods

Surgically resected UPS samples were stained by immunohistochemistry (IHC) for the following: tumor-associated immune cells (CD3, CD8, CD163, CD20), immune checkpoints (stimulatory: OX40, ICOS; inhibitory: PD-L1, LAG3, IDO1, PD1), and the adenosine pathway (CD73, CD39). Sections were reviewed for the presence of lymphoid aggregates (LA). Clinical data were retrospectively obtained for all samples. The Wilcoxon rank-sum and Kruskal-Wallis tests were used to compare distributions. Correlations between biomarkers were measured by Spearman correlation. Univariate and multivariate Cox models were used to identify biomarkers associated with overall survival (OS) and disease-free survival (DFS). Unsupervised clustering was performed, and Kaplan-Meier curves and log-rank tests used for comparison of OS and DFS between immune clusters.

Results

Samples analyzed (n=105) included 46 primary tumors, 34 local recurrences, and 25 metastases. LA were found in 23% (n=10/43), 17% (n=4/24), and 30% (n=7/23) of primary, recurrent, and metastatic samples, respectively. In primary UPS, CD73 expression was significantly higher after preoperative radiation therapy (p=0.009). CD39 expression was significantly correlated with PD1 expression (primary: p=0.002, recurrent: p=0.004, metastatic: p=0.001), PD-L1 expression (primary: p=0.009), and CD3+ cell densities (primary: p=0.016, recurrent: p=0.043, metastatic: p=0.028). In recurrent tumors, there was a strong correlation between CD39 and CD73 (p=0.015), and both were also correlated with CD163+ cell densities (CD39 p=0.013; CD73 p<0.001). In multivariate analyses, higher densities of CD3+ and CD8+ cells (Cox Hazard Ratio [HR]=0.33; p=0.010) were independently associated with OS (CD3+, HR=0.19, p<0.001; CD8+, HR= 0.33, p=0.010) and DFS (CD3+, HR=0.34, p=0.018; CD8+, HR=0.34, p= 0.014). Unsupervised clustering of IHC values revealed three immunologically distinct clusters: immune high, intermediate, and low. In primary tumors, these clusters were significantly associated with OS (log-rank p<0.0001) and DFS (p<0.001).

Conclusion

We identified three immunologically distinct clusters of UPS Associated with OS and DFS. Our data support further investigations of combination anti-PD-1/PD-L1 and adenosine pathway inhibitors in UPS.