Frontiers in Oncology (Oct 2022)

The immune landscape of undifferentiated pleomorphic sarcoma

  • Rossana Lazcano,
  • Carmelia M. Barreto,
  • Ruth Salazar,
  • Fernando Carapeto,
  • Raymond S. Traweek,
  • Cheuk H. Leung,
  • Swati Gite,
  • Jay Mehta,
  • Davis R. Ingram,
  • Khalida M. Wani,
  • Kim-Anh T. Vu,
  • Edwin R. Parra,
  • Wei Lu,
  • Jianling Zhou,
  • Russell G. Witt,
  • Brandon Cope,
  • Prapassorn Thirasastr,
  • Heather Y. Lin,
  • Christopher P. Scally,
  • Anthony P. Conley,
  • Ravin Ratan,
  • J. Andrew Livingston,
  • Alexandra M. Zarzour,
  • Joseph Ludwig,
  • Dejka Araujo,
  • Vinod Ravi,
  • Shreyaskumar Patel,
  • Robert Benjamin,
  • Jennifer Wargo,
  • Ignacio I. Wistuba,
  • Ignacio I. Wistuba,
  • Ignacio I. Wistuba,
  • Neeta Somaiah,
  • Christina L. Roland,
  • Emily Z. Keung,
  • Luisa Solis,
  • Wei-Lien Wang,
  • Alexander J. Lazar,
  • Alexander J. Lazar,
  • Alexander J. Lazar,
  • Elise F. Nassif

DOI
https://doi.org/10.3389/fonc.2022.1008484
Journal volume & issue
Vol. 12

Abstract

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IntroductionUndifferentiated 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 methodsSurgically 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.ResultsSamples 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).ConclusionWe 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.

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