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. ConleyRavin Ratan, J. Andrew Livingston, Alexandra M. Zarzour, Joseph Ludwig, Dejka Araujo, Vinod Ravi, Shreyaskumar Patel, Robert S Benjamin, Jennifer Wargo, Ignacio I. Wistuba, Neeta Somaiah, Christina L. Roland, Emily Z. Keung, Luisa Solis, Wei Lien Wang, Alexander J. Lazar, Elise F. Nassif

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

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.

Original languageEnglish (US)
Article number1008484
JournalFrontiers in Oncology
Volume12
DOIs
StatePublished - Oct 12 2022

Keywords

  • adenosine pathway
  • immune checkpoint inhibitors
  • immune microenvironment
  • tertiary lymphoid structures
  • undifferentiated pleomorphic sarcoma

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

MD Anderson CCSG core facilities

  • Biostatistics Resource Group

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